Systems and methods for automated respirator

ABSTRACT

There is provided a computing device comprising: at least one processor; and a memory comprising instructions that, when executed by the at least one processor, cause the at least one processor to: receive first sensor data indicative of a gas characteristic in a sealed space formed by a face of a wearer and a negative pressure reusable respirator; receive second sensor data indicative of a position of at least one valve in the negative pressure reusable respirator; determine comparative data by comparing the first sensor data to the second sensor data; and perform one or more actions in response to the comparative data. There is also provided a system using such computing device.

TECHNICAL FIELD

The present disclosure relates to systems and methods for automatedrespirators, including sensing of gas characteristics and valve positionwithin respirators and notifications related thereto.

BACKGROUND

Many work environments include hazards that may expose people workingwithin a given environment to a safety event, such as a fall, breathingcontaminated air, or temperature related injuries (e.g., heat stroke,frostbite, etc.). In many work environments, workers may utilizepersonal protective equipment (PPE) to help mitigate the risk of asafety event. Often, a worker may not recognize an impending safetyevent until the environment becomes too dangerous or the worker's healthdeteriorates too far. PPE that fits or is donned by a worker properly isimportant to help mitigate the risk of a safety event.

As used in industry language, a respirator worker seal check, alsoreferred to as a user seal check or a wearer seal check, is a process bywhich a worker donning a respirator assesses the fit of theirtight-fitting respirator for large-scale leaks. As defined by manyregulatory bodies, including the US Occupational Safety and HealthAdministration (OSHA), a respirator worker seal check is distinctlydifferent from a respirator fit test. A respirator fit test is anassessment of worker's suitability to fit a specific make and model ofrespirator, with the test administered by a trained person. Examples ofrespirator fit tests are 3M Qualitative Respirator Fit Tests usingBitrex and/or Saccharin, the TSI PortaCount test. A worker seal check isintended to be a check carried out by a user (i.e. a worker or wearerdonning the respirator), not requiring supervision by any other person,every time the user dons the respirator for use.

Worker seal checks are conducted as either negative seal checks,positive seal checks, or both on tight fitting respirators. The processinvolves the worker using their hands, or a mechanism on the respirator,to cover the inhalation/exhalation flow path(s) and theninhaling/exhaling to create a decrease/increase in pressure in therespirator. Workers assess adequate fit of the respirator based on theirsubjective assessment of how well the respirator holds pressure, thefeeling of air flow around the seal, and the like.

A worker seal check helps inform a worker that they assembled and donnedthe respirator correctly, and as such, should be conducted every time aworker dons a respirator. However, workers sometimes fail or forget toconduct a worker seal check. Additionally, workers often desireadditional confidence in the fit of their respirator, beyond their ownsubjective assessment of the worker seal check.

SUMMARY

In general, the present disclosure describes system comprising anegative pressure reusable respirator configured to be worn by a wearerand to cover at least a mouth and a nose of the wearer to form a sealedspace formed by a face of the wearer and the negative pressure reusablerespirator, wherein the negative pressure reusable respirator comprisesat least one valve; a first sensor configured to generate first sensordata indicative of a gas characteristic in a sealed space formed by aface of the wearer and the negative pressure reusable respirator; asecond sensor configured to generate second sensor data indicative of aposition of the at least one valve; and at least one computing deviceconfigured to provide comparative data by comparing the first sensordata to the second sensor data.

In another aspect, the present disclosure provides a computing devicecomprising: at least one processor; and a memory comprising instructionsthat, when executed by the at least one processor, cause the at leastone processor to: receive first sensor data indicative of a gascharacteristic in a sealed space formed by a face of a wearer and anegative pressure reusable respirator; receive second sensor dataindicative of a position of at least one valve in the negative pressurereusable respirator; determine comparative data by comparing the firstsensor data to the second sensor data; and perform one or more actionsin response to the comparative data.

The details of one or more examples of the disclosure are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the disclosure will be apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

By way of example only, embodiments of the present disclosure will nowbe described below with reference to the accompanying drawings, inwhich:

FIGS. 1A and 1B are a front perspective views of a wearer donning afull-face negative pressure reusable respirator having an accessoryaccording to some embodiments of the present disclosure.

FIG. 2 is a front perspective view of a negative pressure reusablerespirator having an accessory according to some embodiments of thepresent disclosure;

FIGS. 3A and 3B are a front perspective views of a wearer donning ahalf-face negative pressure reusable respirator having an accessoryaccording to some embodiments of the present disclosure.

FIG. 4A is an interior perspective view of a portion of a negativepressure reusable respirator according to some embodiments of thepresent disclosure.

FIG. 4B is an interior perspective view of a portion of a negativepressure reusable respirator according to some embodiments of thepresent disclosure in which a computing device is physically coupled toa sensor.

FIG. 4C is an interior perspective view of a portion of a half-facenegative pressure reusable respirator according to some embodiments ofthe present disclosure.

FIG. 4D is an interior perspective view of a portion of a negativepressure reusable respirator having an electromagnetic waveguideaccording to some embodiments of the present disclosure

FIG. 5 is a block diagram illustrating an example system that includes anegative pressure reusable respirator and a personal protectionequipment management system, in accordance with various techniques ofthis disclosure.

FIG. 6 shows first sensor data as air pressure data over time frominside an exemplary negative pressure reusable respirator according tothe present disclosure when is being worn, when it is not being worn,and during wearer seal checks.

FIG. 7 is a block diagram illustrating, in detail, an operatingperspective of the personal protection equipment management system shownin FIG. 5.

FIG. 8 is a conceptual diagram illustrating an example negative pressurereusable respirator, in accordance with various techniques of thisdisclosure.

FIG. 9 is a plot of first and second sensor data according to thepresent disclosure as a function of time.

FIG. 10 is a plot of a comparison of first and second sensor dataaccording to the present disclosure as a function of time.

FIG. 11 is a plot of a comparison of first and second sensor dataaccording to the present disclosure as a function of time used todetermine physical state and usage information.

FIG. 12 is a plot of a comparison of first and second sensor dataaccording to the present disclosure as a function of time used todetermine occurrence of wearer seal checks.

FIG. 13 is a flowchart illustrating example operations of an examplecomputing system, in accordance with various techniques of the presentdisclosure.

FIG. 14 is a flowchart illustrating example operations of an examplecomputing system, in accordance with various techniques of the presentdisclosure.

FIG. 15 is an interior perspective view of a portion of a negativepressure reusable respirator according to some embodiments of thepresent disclosure in which a computing device is operably coupled to apressure sensor and at least one other sensor.

FIG. 16 illustrates sensor data in accordance with techniques of thisdisclosure.

FIG. 17 illustrates sensor data in accordance with techniques of thisdisclosure.

FIG. 18 illustrates sensor data in accordance with techniques of thisdisclosure.

FIG. 19 illustrates sensor data in accordance with techniques of thisdisclosure.

FIG. 20 illustrates sensor data in accordance with techniques of thisdisclosure.

It is to be understood that the embodiments may be used and structuralchanges may be made without departing from the scope of the presentdisclosure. The figures are not necessarily to scale. Like numbers usedin the figures refer to like components. However, it will be understoodthat the use of a number to refer to a component in a given figure isnot intended to limit the component in another figure labeled with thesame number.

DETAILED DESCRIPTION

Before any embodiments of the present disclosure are explained indetail, it is to be understood that the present disclosure is notlimited in its application to the details of construction and thearrangement of components set forth in the following description. Thepresent disclosure is capable of other embodiments and of beingpracticed or of being carried out in various ways. Also, it is to beunderstood that the phraseology and terminology used herein is for thepurpose of description and should not be regarded as limiting. The useof “including,” “comprising,” or “having” and variations thereof hereinis meant to encompass the items listed thereafter and equivalentsthereof as well as additional items. Any numerical range recited hereinincludes all values from the lower value to the upper value. Forexample, if a percentage is stated as 1% to 50%, it is intended thatvalues such as 2% to 40%, 10% to 30%, or 1% to 3%, etc., are expresslyenumerated. These are only examples of what is specifically intended,and all possible combinations of numerical values between and includingthe lowest value and the highest value enumerated are considered to beexpressly stated in this application.

In the present detailed description, reference is made to theaccompanying drawings, which illustrate specific embodiments in whichthe presently disclosed devices may be practiced. The illustratedembodiments are not intended to be exhaustive of all embodimentsaccording to the present disclosure. It is to be understood that otherembodiments may be utilized and structural or logical changes may bemade without departing from the scope of the present disclosure. Thefollowing detailed description, therefore, is not to be taken in alimiting sense, and the scope of the present disclosure is defined bythe appended claims.

Unless otherwise indicated, all numbers expressing feature sizes,amounts, and physical properties used in the specification and claimsare to be understood as being modified in all instances by the term“about.” Accordingly, unless indicated to the contrary, the numericalparameters set forth in the foregoing specification and attached claimsare approximations that can vary depending upon the desired propertiessought to be obtained by those skilled in the art utilizing theteachings disclosed herein.

As used in this specification and the appended claims, the singularforms “a,” “an,” and “the” encompass embodiments having pluralreferents, unless the content clearly dictates otherwise. As used inthis specification and the appended claims, the term “or” is generallyemployed in its sense including “and/or” unless the content clearlydictates otherwise.

Spatially related terms, including but not limited to, “proximate,”“distal,” “lower,” “upper,” “beneath,” “below,” “above,” and “on top,”if used herein, are utilized for ease of description to describe spatialrelationships of an element(s) to another. Such spatially related termsencompass different orientations of the device in use or operation inaddition to the particular orientations depicted in the figures anddescribed herein. For example, if an object depicted in the figures isturned over or flipped over, portions previously described as below orbeneath other elements would then be above or on top of those otherelements.

As used herein, terms “worker”, “wearer” and “user” are usedinterchangeably.

The term “operably disposed” as used herein means that a component isdirectly or indirectly and removably or fixedly attached to anothercomponent. As used herein, when an element, component, or layer forexample is described as forming a “coincident interface” with, or being“on,” “connected to,” “coupled with,” “stacked on” or “in contact with”another element, component, or layer, it can be directly on, directlyconnected to, directly coupled with, directly stacked on, in directcontact with, or intervening elements, components or layers may be on,connected, coupled or in contact with the particular element, component,or layer, for example.

Throughout the present disclosure where negative pressure reusablerespirators is being referred to disclosure is applicable to full andhalf face negative pressure reusable respirators, full and half facepositive pressure reusable respirators, and self-contained breathingapparatus.

As shown in FIGS. 1A and 1B, the present disclosure provides a negativepressure reusable respirator 13 configured to be worn by a wearer 10 andto cover at least a mouth and a nose of the wearer 10 to form a sealedspace formed by a face of the wearer 10 and the negative pressurereusable respirator 13. Negative pressure reusable respirators 13 usefulin the present disclosure include at least one valve operably connectedto at least one contaminant capture device 23.

As shown in FIG. 2, the presently disclosed negative pressure reusablerespirator 10 also includes at least one accessory 11. In someembodiments, accessory 11 is operably disposed within the sealed space.In some embodiments, accessory 11 is operably disposed on an externalsurface of the negative pressure reusable respirator 13. In someembodiments, accessory 11 includes a computing device 300 (as shown inFIG. 8). In some embodiments, accessory 11 includes at least one outputdevice, such as for example, a speaker, a haptic device, a light, agraphic display device, and the like. Referring again to FIGS. 1A and1B, after wearer 10 dons negative pressure reusable respirator 13,he/she can apply pressure to at least one contaminant capture device 23,in some embodiments two contaminant capture devices 23, inhales and holdhis/her breath or continue to inhale to maintain a negative pressure. Insome embodiment, after a course of events, such as those presentlydisclosed below, the output device of accessory 11 provides at least onealert to wearer 10.

Referring to FIG. 3, in some embodiments, negative pressure reusablerespirator 13 includes at least one valve 9. In some examples, a firstsensor 3 is disposed proximate at least one valve 9. In some examples, asecond sensor 5 is disposed proximate at least one valve 9. In someembodiments, both first sensor 3 and second sensor 5 are disposedproximate at least one valve 9. First sensor 3 is configured to generatefirst sensor data indicative of a gas characteristic of negativepressure reusable respirator 13 and second sensor 5 is configured togenerate second sensor data indicative of a position of at least onevalve 9 of negative pressure reusable respirator 13.

FIG. 5 is a block diagram illustrating an example system 2 that is apersonal protective equipment management system (PPEMS) 6 for providinganalytics and alerting of safety events for at least one negativepressure reusable respirator (i.e., 13A), and in some embodiments, for aplurality of negative pressure reusable respirators 13A-13N, accordingto techniques described in this disclosure. For example, each ofnegative pressure reusable respirators 13A-13N (collectively, negativepressure reusable respirators 13) include at least two sensors, wherethe first sensor is configured to generate first sensor data indicativeof a gas characteristic of the respective negative pressure reusablerespirators 13 and where the second sensor is configured to generatesecond sensor data indicative of a position of at least one valve of therespective negative pressure reusable respirators 13. In someembodiments, system 2 may also include at least one computing devices(e.g., PPEMS 6, hubs 14, accessories 11, among others), where the atleast one computing device is configured to provide comparative data bycomparing the first sensor data to the second sensor data. As used inthis disclosure, the gas characteristic is selected from at least one ofair pressure, gas composition, temperature, gas flow rate, andcombinations thereof.

According to techniques of this disclosure, the at least one computingdevice, such as PPEMS 6, monitors usage to, at least in part, use thecomparative data to determine at least one physical state of thenegative pressure reusable respirator. In some embodiments, PPEMS 6monitors gas characteristics in a sealed space formed by a face of thewearer and the negative pressure reusable respirator 13 and positions ofthe at least one valve in the negative pressure reusable respirator 13to determine at least one physical state of the negative pressurereusable respirator 13. In some examples, the physical state may beselected from at least one of: presence of physical components of thenegative pressure reusable respirator; performance metrics of physicalcomponents of the negative pressure reusable respirator; pressure dropof the negative pressure reusable respirator; pressure drop of thenegative pressure reusable respirator at different air flow ratesthrough the respirator; ambient temperature; temperature within thenegative pressure reusable respirator; composition of ambient gases inthe workplace; composition of gases within the negative pressurereusable respirator; and any combinations thereof. In some embodiments,the at least one computing device is further configured to determine achange in at least one physical state of the negative pressure reusablerespirator 13.

According to techniques of this disclosure, the at least one computingdevice, such as PPEMS 6, monitors usage to, at least in part, use thecomparative data to determine usage information related to the negativepressure reusable respirator 13. In some embodiments, PPEMS 6 monitorsgas characteristics in a sealed space formed by a face of the wearer andthe negative pressure reusable respirator 13 and positions of the atleast one valve in the negative pressure reusable respirator 13 todetermine usage information related to the negative pressure reusablerespirator 13. In some examples, usage information is selected from atleast one of: respiration through the at least one valve; occlusion ofan inhalation path of the negative pressure reusable respirator 13;occlusion of an exhalation path of the negative pressure reusablerespirator 13; occurrence of a wearer seal check; information related toa performance procedure of a wearer seal check; information related toquality of a seal formed by the face of the wearer and the negativepressure reusable respirator 13; change in the seal formed by the faceof the wearer and the negative pressure reusable respirator 13; and anycombination thereof. In some examples, respiration through the at leastone valve includes steps of donning of the negative pressure reusablerespirator 13 and doffing of the negative pressure reusable respirator13. In some embodiments, the information related to a performanceprocedure of a wearer seal check is selected from at least one of:duration of time related to a wearer seal check; pressure related to awearer seal check; occlusion of an inhalation path of the negativepressure reusable respirator 13; occlusion of an exhalation path of thenegative pressure reusable respirator 13; and any combination thereof.

The presently disclosed second sensor may include an electromagneticradiation emitter and an electromagnetic radiation detector. In someembodiments, the electromagnetic radiation emitter may comprise a lightemitting diode, a laser diode, an incandescent bulb, or other suchdevice configured to generate electromagnetic radiation. In someembodiments, an electromagnetic radiation detection may comprise aphoto-sensitive diode, a bolometer, a photosensitive diode array, acharge-coupled device, an As shown in FIG. 4D, in some embodiments, thesecond sensor further includes an electromagnetic waveguide 22 structureconfigured to transmit electromagnetic radiation from theelectromagnetic radiation emitter to the at least one valve of thenegative pressure reusable respirator 13, and from the at least onevalve to the electromagnetic radiation detector. In some embodiments,the electromagnetic waveguide 22 structure may comprise a plurality ofelectromagnetic waveguides.

As shown in the example of FIG. 5, system 2 represents a computingenvironment in which computing device(s) within a plurality of physicalenvironments 8A, 8B (collectively, environments 8) electronicallycommunicate with PPEMS 6 via one or more computer networks 4. Each ofphysical environment 8 represents a physical environment, such as a workenvironment, in which one or more individuals, such as workers 10, usepersonal protective equipment, such as a negative pressure reusablerespirator 13 while engaging in tasks or activities within therespective environment. Example environments 8 include constructionsites, mining sites, manufacturing sites, among others.

In this example, environment 8A is shown as generally as having workers10, while environment 8B is shown in expanded form to provide a moredetailed example. In the example of FIG. 5, a plurality of workers10A-10N are shown as utilizing personal protective equipment (PPE), suchas negative pressure reusable respirators 13. As used throughout thisdisclosure, negative pressure reusable respirators 13 include anyreusable respirator in which the air pressure inside the facepiece isless than the ambient air pressure (e.g., the pressure of the airoutside the respirator) during inhalation. Although respirators 13 inthe example of FIG. 5 are illustrated as negative-pressure reusablerespirators, the techniques described herein apply to other types ofrespirators, such as positive pressure reusable respirators, disposablerespirators, or powered-air purifying respirators. As used throughoutthis disclosure, a positive pressure respirator includes any respiratorin which the air pressure inside the facepiece is greater than theambient air pressure. Negative pressure reusable respirators 13 includea facepiece (e.g., a full facepiece, or a half facepiece) configured tocover at least a worker's nose and mouth. For example, a half facepiecemay cover a worker's nose and mouth and a full facepiece may cover aworker's eyes, nose, and mouth. Negative pressure reusable respirators13 may fully or partially (e.g., 75%) cover a worker's head. Negativepressure reusable respirators 13 may include a head harness (e.g., anelastic strap) that secures negative pressure reusable respirators 13 tothe back of the worker's head.

Again, as shown in examples depicted in FIGS. 1A, 1B, 2 and 3, physicalcomponents of the negative pressure reusable respirator 13 may includeone or more valves 9, one or more contaminant capture devices 23, onemore removable accessory 11, and any combinations thereof. In someexamples, negative pressure reusable respirators 13 are configured toreceive contaminant capture devices 23A-23N (collectively, contaminantcapture devices 23). Contaminant capture devices 23 are configured toremove contaminants from air as air is drawn through the contaminantcapture device (e.g., when a worker wearing a reusable respiratorinhales). Contaminant capture devices 23 include particulate filters,chemical cartridges, or combination particulate filters/chemicalcartridges. As used throughout this disclosure, particulate filters areconfigured to protect a worker from particulates (e.g., dust, mists,fumes, smoke, mold, bacteria, etc.). Particulate filters captureparticulates through impaction, interception, and/or diffusion. As usedthroughout this disclosure, chemical cartridges are configured toprotect a worker from gases or vapors. Chemical cartridges may includesorbent materials (e.g., activated carbon) that react with a gas orvapor to capture the gas or vapor and remove the gas or vapor from airbreathed by a worker. For instance, chemical cartridges may captureorganic vapors, acid gasses, ammonia, methylamine, formaldehyde, mercuryvapor, chlorine gas, among others.

In some embodiments, contaminant capture devices 23 may be removable. Inother words, a worker may remove a contaminant capture device from anegative pressure reusable respirator 13 (e.g., upon the contaminantcapture device reaching the end of its expected lifespan) and install adifferent (e.g., unused, new) contaminant capture device to therespirator. In some examples, the particulate filters or chemicalcartridges have a limited service life. In some examples, when achemical cartridge is exhausted (e.g., captures a threshold amount ofgas or vapors), gases or vapors may pass through the chemical cartridgeto the worker (which is called “breakthrough”). In some examples, asparticulate filters become saturated with a contaminant, the filterbecomes harder to pull air through, thus making the worker inhale deeperto breathe.

Each of negative pressure reusable respirators 13 include, in someexamples, embedded sensors or monitoring devices and processingelectronics configured to capture data in real-time as a worker (e.g.,wearer) engages in activities while utilizing (e.g., wearing) therespirator. Negative pressure reusable respirators 13 include a numberof sensors for sensing operational characteristics of the respirators13. For example, the first sensor useful in presently disclosed negativepressure reusable respirators 13 include an air pressure sensorconfigured to detect the air pressure in the cavity formed between therespirator and the worker's face, which detect the air pressure withinthe cavity as the worker 10 breathes (e.g., inhales and exhales). Inother words, the air pressure sensors detect the air pressure within thesealed space (also referred to as a cavity, or respirator cavity) formedby a face of the wearer and the negative pressure reusable respirator13.

In addition, in some embodiments, each of negative pressure reusablerespirators 13 may include one or more computing devices, 60, 300 thatare configured to provide comparative data by comparing the first sensordata to the second sensor data to determine the physical state of thenegative pressure reusable respirator. For example, the first sensordata providing air pressure within the sealed space is compared to thesecond sensor data providing valve position to determine the performanceof physical components of the negative reusable respirator. In someembodiments, as shown in FIG. 8, computing device 300 is operablydisposed within accessory 11, where accessory 11 is operably disposedwithin a sealed space formed by a face of the wearer and the negativepressure reusable respirator 13A.

FIG. 10 shows exemplary first sensor data and second sensor data plottedwith respect to time, where first and second sensor data was generatedby exemplary first and second sensors according to the presentdisclosure, and where the first sensor data indicates air pressurewithin the sealed space formed by the face of a wearer and a negativepressure reusable respirator, and second sensor data indicates positionof at least one valve in the negative pressure reusable respirator.

In addition, in some embodiments, each of negative pressure reusablerespirators 13 may include one or more computing devices 300 that areconfigured to provide comparative data by comparing the first sensordata to the second sensor data to determine usage information related tothe negative pressure reusable respirator. For example, as shown inFIGS. 10, 11 and 12, the first sensor data providing air pressure withinthe sealed space is compared to the second sensor data providing valveposition to determine usage information selected from at least one of:respiration through the at least one valve, occlusion of an inhalationpath of the negative pressure reusable respirator; occlusion of anexhalation path of the negative pressure reusable respirator; occurrenceof a wearer seal check; information related to a performance procedureof a wearer seal check; information related to quality of a seal formedby the face of the wearer and the negative pressure reusable respirator;change in the seal formed by the face of the wearer and the negativepressure reusable respirator; and any combinations thereof.

In addition, each of negative pressure reusable respirators 13 mayinclude one or more output devices for outputting data that isindicative of operation of negative pressure reusable respirator 13and/or generating and outputting communications to the respective worker10. For example, negative pressure reusable respirators 13 may includeone or more devices to generate audible feedback (e.g., one or morespeakers), visual feedback (e.g., one or more displays, light emittingdiodes (LEDs) or the like), or tactile feedback (e.g., a device thatvibrates or provides other haptic feedback). In some embodiments, suchfeedback is provided in the form of at least one alert selected from: anaudible alert, a visual alert, a haptic alert, a text alert, or anycombination thereof. In some embodiments, the output device is operablydisposed on presently disclosed accessory 11.

In some examples, at least one computing device 16, 18, 60, 300 isconfigured to perform one or more actions by at least in part beingconfigured to: output a notification to a second computing device;output an alert to a wearer of a negative pressure reusable respirators13; output to another wearer in a proximal environment; or a combinationthereof. In some examples, the alert is selected from at least one of anaudible alert, a visual alert, a haptic alert, a text alert, or acombination thereof.

In some examples, at least one computing device 16, 18, 60, 300 isconfigured to output an alert in response to the comparative data. Insome examples, at least one computing device 16, 18. 60, 300 isconfigured to output an alert in response to determining thatrespiration occurred through the at least one valve and a wearer sealcheck was not performed. In some examples, the output is selected fromat least one of: a notification to the wearer to perform a seal check; anotification to another computing device that the wearer failed toperform a seal check; a notification to another wearer in a proximalenvironment; or a combination thereof. In some examples, if anotification to the wearer to perform a seal check was provided to thewearer, the output is alterable. For example, the at least one computingdevice 16, 18, 60, 300 may output alert notifications to the wearer toperform a seal check in the form of lights and vibrations to the wearer.

In some examples, at least one computing device 16, 18, 60, 300 isconfigured to output an alert to the wearer in response to determiningthat respiration occurred through that at least one valve and a wearerseal check was performed. In some examples, the output is selected fromat least one of: a notification that the wearer is performing a sealcheck related to the quality of seal of the negative pressure reusablerespirator on the wearer's face; a notification that the wearerperformed a seal check related to the quality of seal of the negativepressure reusable respirator on the wearer's face that satisfied atleast one threshold; a notification that the wearer performed a sealcheck related to the quality of seal of the negative pressure reusablerespirator on the wearer's face that did not satisfy at least onethreshold; or a combination thereof. In some examples, if notificationthat the wearer performed a seal check related to the quality of seal ofthe negative pressure reusable respirator on the wearer's face thatsatisfied at least one threshold is provided to the wearer, the alert isdiscontinued. In some examples, if notification that the wearerperformed a seal check related to the quality of seal of the negativepressure reusable respirator on the wearer's face that did not satisfyat least one threshold is provided to the wearer, the alert is altered.In some embodiments, the alert is altered by altering at least one ofintensity of the alert, frequency of the alert, tone of the alert,pattern of the alert, color of the alert, display of the alert, contentof the alert, or a combination thereof. For example, the at least onecomputing device 16, 18, 60, 300 may output alert notifications to thewearer to perform a seal check in the form of lights and vibrations tothe wearer. The at least one computing device 16, 18, 60, 300 may thenalter the alert, or provide an additional alert that the wearer isperforming a seal check related to the quality of seal of the negativepressure reusable respirator on the wearer's face. The at least onecomputing device 16, 18, 60, 300 may then alter the alert, or provide anadditional alert, or discontinue the alert, or a combination thereof,that the wearer performed a seal check related to the quality of seal ofthe negative pressure reusable respirator on the wearer's face thatsatisfied at least one threshold. Alternatively, the at least onecomputing device 16, 18, 60, 300 may then alter the alert, or provide anadditional alert, or discontinue the alert, or a combination thereof,that the wearer performed a seal check related to the quality of seal ofthe negative pressure reusable respirator on the wearer's face that didnot satisfy at least one threshold. For example, the at least onecomputing device 16, 18, 60, 300 may alter the alert in response to thewearer performed a seal check related to the quality of seal of thenegative pressure reusable respirator on the wearer's face that did notsatisfy at least one threshold, and then revert to the alert to thewearer to perform a seal check.

In some examples, computing device 16, 18, 60, 300 may automaticallydetermine that negative pressure reusable respirator 13 is being worn bya wearer 10. For example, computing device 16, 18, 60, 300 may receivefirst sensor data, such as air pressure data, indicative of the airpressure in the sealed space formed by a face of the wearer and thenegative pressure reusable respirator 13 from a first sensor 3, whereinthe air pressure data meets a set of predetermined thresholds. Forexample, FIG. 6 shows first sensor data as air pressure data over timefrom inside an exemplary negative pressure reusable respirator 13according to present disclosure when it is being worn, when it is notbeing worn, and during wearer seal checks. For example, a computingdevice 16, 18, 60, 300 may determine that a negative pressure reusablerespirator 300 transitioned from a state of not being worn by a wearerto being worn by a wearer when the pressure data over time meets athreshold number of peaks (increase in pressure) or valleys (decrease inpressure) that meet a threshold pressure change (positive or negative)in a threshold amount of time. For example, when the air pressure datameasured from first sensor 3 indicates three differential pressurechanges (pressure difference between the air pressure in the sealedspace formed by a face of wearer 10 and negative pressure reusablerespirator 13 and the ambient pressure) below −100 Pascals in less thanthirty seconds, computing device 16, 18, 60, 300 may determine thatnegative pressure reusable respirator 13 transitioned from a state ofnot being worn by a wearer 10 to being worn by a wearer 10. This enablescomputing device 16, 18, 60, 300 to determine that respirator 13 isbeing worn by wearer 10 without any additional action from wearer 10beyond donning respirator 13. As a beneficial result, wearer 10 does nothave to be trained or remember to take an action to initiate computingdevice 16, 18, 60, 300. Devices that do not automatically determinedonning and wear of respirator 13 may require a trained user action suchas interacting directly with computing device 16, 18, 60, 300 orcovering contaminant capture devices 23 and inhaling sharply to generatea specific sensor signal, or other such examples that require a traineduser action, to initiate computing device 16, 18, 60, 300.

In some examples, after computing device 16, 18, 60, 300 determined thata negative pressure reusable respirator 13 is being worn by a wearer 10,computing device 16, 18, 60, 300 may perform one or more actions asindicated by one or more safety rules. In some examples, computingdevice 16, 18, 60, 300 may perform one or more actions immediately upondetermining that a negative pressure reusable respirator 13 is beingworn by wearer 10, at a time after determining that a negative pressurereusable respirator 13 is being worn by a wearer 10, or at a pluralityof times.

In some examples, safety rules may be retrieved from a memory modulephysically coupled to computing device 16, 18, 60, 300. In someexamples, the safety rules may be retrieved from a device physicallyseparate from computing device 16, 18, 60, 300, such as via wirelesscommunication to another device. In some examples, the safety rules maybe related to the performance of a wearer seal check by wearer 10. Forexample, after computing device 16, 18, 60, 300 detected that the wearer10 donned respirator 13, computing device 16, 18, 60, 300 may initiate apattern of alerts to wearer 10 until a wearer seal check is performed.In one example, the alerts may take the form of a pattern of vibrationsand/or lights and/or audible signals (such as text content, lights, andthe like) to wearer 10. Computing device 16, 18, 60, 300 may thendetermine that a wearer seal check is being performed based at least inpart on data from the first sensor indicative of a gas characteristic ora combination of the first sensor data and second sensor data indicativeof a position of a valve. In some examples, computing device 16, 18, 60,300 may alter the alert output while the wearer seal check is beingperformed, for example by temporarily turning off the alert while thewearer seal check is being performed. In some example, computing device16, 18, 60, 300 may then generate an alert based on whether or not thewearer seal check satisfied a threshold or a combination of thresholds.In one example, computing device 16, 18, 60, 300 may generate an alertindicating an unsatisfactory seal check if the air pressure or combinedair pressure and valve position data cross a threshold after the wearerseal check has started. For example, if the absolute differential airpressure (difference between the ambient air pressure and the airpressure in the sealed space formed by a face of the wearer and thenegative pressure reusable respirator, either positive or negative)falls below a threshold at any time before a satisfactory wearer sealcheck is determined, the wearer seal check may be determined to beunsatisfactory. In some examples, if an unsatisfactory wearer seal checkis determined, computing device 16, 18, 60, 300 may generate an alertcomprising a pattern of vibrations and/or lights and/or audible and/ortext content signals to the wearer, such as a series of rapid red lightsand vibrations. Following this unsatisfactory wearer seal check alert,computing device 16, 18, 60, 300 may revert the alerts back to the samealerts that were generated after computing device 16, 18, 60, 300determined that respirator 13 entered a state of being worn by a wearer10.

In another instance, if the wearer seal check is determined to besatisfactory by meeting one or more thresholds, computing device 16, 18,60, 300 may generate a different pattern of alerts indicating asatisfactory seal check has been performed. For example, the alerts maytake the form a green light and single long vibration to indicate asatisfactory wearer seal check. In some examples, if a satisfactorywearer seal check is performed, the first set of alerts generated afterdetermining that the respirator is being worn may remain turned off.

In some examples, a satisfactory wearer seal check may require wearer 10to continually exert either positive or negative pressure intorespirator 13 to achieve the required threshold. In these examples, asatisfactory wearer seal check may be determined if the air pressure orcombined air pressure and valve position data cross a threshold afterthe wearer seal check has started. For example, if the absolutedifferential air pressure (difference between the ambient air pressureand the air pressure in the sealed space formed by a face of the wearerand the negative pressure reusable respirator, either positive ornegative pressure) is maintained above or below a threshold for apredetermined period, such as a period of time, the wearer seal checkedmay be determined to be satisfactory. In another example, the period maynot be predetermined, and may instead be a dynamic period depending onthe magnitude of the air pressure. For example, the threshold requiredto achieve a satisfactory wearer seal check may be a time integration ofthe air pressure during a wearer seal check, such that when a cumulativecombination of time and pressure exceeds a threshold, the wearer sealcheck is determined to be satisfactory.

In some examples, a satisfactory wearer seal check may require wearer 10to either inhale or exhale into the respirator and then hold theirbreath. In these examples, the threshold required to achieve asatisfactory wearer seal check may be based on a change in air pressureor change in the combination of air pressure and valve position dataover time. For example, a rapid decay in the absolute different airpressure, after inhaling or exhaling, towards the ambient air pressuremay indicate an unsatisfactory seal, whereas a slow decay may indicate asatisfactory seal. In some examples, computing device 16, 18, 60, 300may determine, based at least in part on changes in air pressure dataover time during the wearer seal check, whether wearer 10 is holdingtheir breath, or continuing to exert either positive or negativepressure into the respirator. Computing device 16, 18, 60, 300 may thenuse a different set of thresholds to determine whether or not asatisfactory wearer seal check is achieved, based on the determinationof how the wearer is performing the wearer seal check.

In some examples, computing device 16, 18, 60, 300 may use the same setof thresholds that was used to determine that a negative pressurereusable respirator 13 has transitioned from a state of not being wornby a wearer 10 to a state of being worn by a wearer 10 to additionallydetermine that a negative pressure reusable respirator 13 continues tobe worn by a wearer 10, or transitions from a state of being worn by awearer 10 to not being worn by a wearer 10. In another example,computing device 16, 18, 60, 300 may use a different set of thresholdsto determine that a negative pressure reusable respirator 13 continuesto be worn by a wearer 10, or transitions from a state of being worn bya wearer 10 to not being worn by a wearer 10. For example, if the airpressure, as determined by first sensor 3, has a variability, such as adifference between minimum and maximum values, below a threshold duringa threshold period of time, computing device 16, 18, 60, 300 maydetermine that the negative pressure reusable respirator 13 is no longerbeing worn by a wearer 10. In some examples, the thresholds may be partof predetermined safety rules.

In other examples, the thresholds may by dynamically determined based onmodels based at least in part on the use of respirator 13 and/or wearerinformation. In some examples, if computing device 16, 18, 60, 300determines that respirator 13 is no longer being worn by a wearer 10,and then later determines that respirator 13 is once again being worn bya wearer 10, computing device 16, 18, 60, 300 may restart the previouslydescribed alert sequences related to detecting that respirator 13 isbeing worn by wearer 10 and a satisfactory wearer seal check has notbeen performed. In some examples, the alert sequences may only bestarted again respirator 13 was in a state of not being worn (i.e. wasremoved) for a time greater than threshold period. Said another way, theone or more safety rules may comprise a condition that a respirator sealcheck was performed by wearer 10 before a period of negative pressurereusable respirator 13 being in a state of not being worn by a wearer 10that is less than a predetermined period. In some instances, the set ofthresholds used to determine that respirator 13 is no longer being wornby a wearer 10 may also be used, with the same or different thresholdvalues, to determine that negative pressure reusable respirator 13 doesnot provide an adequate seal to the face of the wearer 10. In someexamples, the threshold values may be relative threshold values. Forexample, if the air pressure variability over time as measured by thefirst sensor rapidly decreases relative to the variability at a previoustime, computing device 16, 18, 60, 300 may determine a loss of adequaterespirator seal. In another example, computing device 16, 18, 60, 300may use a combination of sensor data, or a combination of sensor datathat changes over time, to determine a loss in adequate respirator seal.For example, computing device 16, 18, 60, 300 may determine a loss inrespirator seal at least in part based on a combination of air pressuredata from a first sensor 3 and valve position data from a second sensor5 that change over time. Computing device 16, 18, 60, 300 may then usesimilar alert mechanisms, such as a pattern of vibrations and/or lightsand/or audible signals and/or text content signals to wearer 10 to alertwearer 10 to the loss of respirator seal.

In another example, the combination of sensor data may be a combinationof data from a single sensor over different periods of time. Forexample, computing device 16, 18, 60, 300 may determine periods ofinhalation and periods of exhalation based on data from a first sensor 3indicative of a gas characteristic in a sealed space formed by a face ofwearer 10 and negative pressure reusable respirator 13, and/or data froma second sensor 5 indicative of a valve position. Computing device 16,18, 60, 300 may then compare the data during periods of inhalation tothe data during periods of exhalation and determine changes in therespirator seal based on the comparative data. For example, themagnitude of inhalation pressure relative to ambient pressure comparedto the magnitude of exhalation pressure relative to ambient pressure maychange due to changes in the respirator seal.

In another example, computing device 16, 18, 60, 300 may use acombination of comparative data from a single sensor during differentperiods of time as well as comparative data between different sensors todetermine changes in the respirator seal. In some examples, the ambientpressure may be determined at least in part based on data from firstsensor 3 indicative of a gas characteristic in a sealed space formed bya face of wearer 10 and negative pressure reusable respirator 13. Insome examples, the ambient pressure may be determined by an additionalsensor located external to the sealed space of respirator 13.

In further examples, the previously described examples may use firstsensor data that is different than air pressure, such as a dataindicative of a different gas characteristic of the sealed space formedby a face of the wearer and the negative pressure reusable respirator.For example, temperature, humidity, gas composition, gas flow rates, andothers may be used to create similar thresholds as those described forair pressure data. In other examples, the alerts generated may begenerated to devices or persons other than, or in addition to, thewearer, such as into a memory storage device, or to a separate computingdevice. In some examples, any of the previously described thresholds,safety rules and alert properties may be configurable.

In some embodiments, accessories 11 operably disposed in each ofnegative pressure reusable respirators 13 are configured to communicatedata, such as sensed motions, events and conditions, via wirelesscommunications, such as via 802.11 WiFi® protocols, Bluetooth® protocolor the like. Accessories 11 operably disposed in negative pressurereusable respirators 13 may, for example, communicate directly with awireless access point 19. As another example, each worker 10 may beequipped with a respective one of wearable communication hubs 14A-14Mthat enable and facilitate communication between accessories 11 operablydisposed in negative pressure reusable respirators 13 and PPEMS 6. Forexample, accessories 11 operably disposed in negative pressure reusablerespirators 13 as well as other PPEs (such as fall protection equipment,hearing protection, hardhats, or other equipment) for the respectiveworker 10 may communicate with a respective communication hub 14 viaBluetooth or other short-range protocol, and the communication hubs maycommunicate with PPEMs 6 via wireless communications processed bywireless access points 19. Although shown as wearable devices, hubs 14may be implemented as stand-alone devices deployed within environment8B. In some examples, hubs 14 may be articles of PPE.

In some embodiments, each of environments 8 may include computingfacilities (e.g., a local area network) by which sensing stations 21,beacons 17, and/or accessories 11 operably disposed in negative pressurereusable respirators 13 are able to communicate with PPEMS 6. Forexamples, environments 8 may be configured with wireless technology,such as 802.11 wireless networks, 802.15 ZigBee networks, and the like.In the example of FIG. 5, environment 8B includes a local network 7 thatprovides a packet-based transport medium for communicating with PPEMS 6via network 4. Environment 8B may include wireless access point 19 toprovide support for wireless communications. In some examples,environment 8B may include a plurality of wireless access points 19 thatmay be geographically distributed throughout the environment to providesupport for wireless communications throughout the environment.

In some examples, each worker 10 may be equipped with a respective oneof wearable communication hubs 14A-14N that enable and facilitatewireless communication between PPEMS 6 and sensing stations 21, beacons17, and/or negative pressure reusable respirators 13. For example,sensing stations 21, beacons 17, and/or negative pressure reusablerespirators 13 may communicate with a respective communication hub 14via wireless communication (e.g., Bluetooth® or other short-rangeprotocol), and the communication hubs may communicate with PPEMS 6 viawireless communications processed by wireless access point 19. Althoughshown as wearable devices, hubs 14 may be implemented as stand-alonedevices deployed within environment 8B.

In general, each of hubs 14 is programmable via PPEMS 6 so that localalert rules may be installed and executed without requiring a connectionto the cloud. As such, each of hubs 14 provides a relay of streams ofdata from sensing stations 21, beacons 17, and/or negative pressurereusable respirators 13, and provides a local computing environment forlocalized alerting based on streams of events in the event communicationwith PPEMS 6 is lost.

As shown in the example of FIG. 5, an environment, such as environment8B, may also contain one or more wireless-enabled beacons, such asbeacons 17A-17B, that provide accurate location data within the workenvironment. For example, beacons 17A-17B may be GPS-enabled such that acontroller within the respective beacon may be able to preciselydetermine the position of the respective beacon. Based on wirelesscommunications with one or more of beacons 17, a given accessory 11operably disposed in negative pressure reusable respirator 13, orcommunication hub 14 worn by a worker 10 is configured to determine thelocation of the worker within environment 8B. In this way, event datareported to PPEMS 6 may be stamped with positional data to aid analysis,reporting and analytics performed by PPEMS 6.

In addition, in some embodiments, an environment, such as environment8B, may also include one or more wireless-enabled sensing stations, suchas sensing stations 21A, 21B. Each sensing station 21 includes one ormore sensors and a controller configured to output data indicative ofsensed environmental conditions. Moreover, sensing stations 21 may bepositioned within respective geographic regions of environment 8B orotherwise interact with beacons 17 to determine respective positions andinclude such positional data when reporting environmental data to PPEMS6. As such, PPEMS 6 may be configured to correlate the sensedenvironmental conditions with the particular regions and, therefore, mayutilize the captured environmental data when processing event datareceived from negative pressure reusable respirators 13, or sensingstations 21. For example, PPEMS 6 may utilize the environmental data toaid generating alerts or other instructions for negative pressurereusable respirators 13 and for performing predictive analytics, such asdetermining any correlations between certain environmental conditions(e.g., temperature, humidity, visibility) with abnormal worker behavioror increased safety events. As such, PPEMS 6 may utilize currentenvironmental conditions to aid prediction and avoidance of imminentsafety events. Example environmental conditions that may be sensed bysensing stations 21 include but are not limited to temperature,humidity, presence of gas, pressure, visibility, wind and the like.Safety events may refer to heat related illness or injury, cardiacrelated illness or injury, respiratory related illness or injury, or eyeor hearing related injury or illness.

In example implementations, an environment, such as environment 8B, mayalso include one or more safety stations 15 distributed throughout theenvironment. Safety stations 15 may allow one of workers 10 to check outnegative pressure reusable respirators 13 and/or other safety equipment,verify that safety equipment is appropriate for a particular one ofenvironments 8, and/or exchange data. Safety stations 15 may enableworkers 10 to send and receive data from sensing stations 21, and/orbeacons 17. For example, safety stations 15 may transmit alert rules,software updates, or firmware updates to negative pressure reusablerespirators 13 or other equipment, such as sensing stations 21, and/orbeacons 17. Safety stations 15 may also receive data cached on negativepressure reusable respirators 13, hubs 14, sensing stations 21, beacons17, and/or other safety equipment. That is, while equipment such assensing stations 21, beacons 17, negative pressure reusable respirators13, and/or data hubs 14 may typically transmit data via network 4 inreal time or near real time, such equipment may not have connectivity tonetwork 4 in some instances, situations, or conditions. In such cases,sensing stations 21, beacons 17, negative pressure reusable respirators13, and/or data hubs 14 may store data locally and transmit the data tosafety stations 15 upon regaining connectivity to network 4. Safetystations 15 may then obtain the data from sensing stations 21, beacons17, negative pressure reusable respirators 13, and/or data hubs 14.

In addition, each of environments 8 may include computing facilitiesthat provide an operating environment for end-worker computing devices16 for interacting with PPEMS 6 via network 4. For example, each ofenvironments 8 typically includes one or more safety managersresponsible for overseeing safety compliance within the environment. Ingeneral, each worker 20 interacts with computing devices 16 to accessPPEMS 6. Each of environments 8 may include systems. Similarly, remoteworkers may use computing devices 18 to interact with PPEMS 6 vianetwork 4. For purposes of example, the end-worker computing devices 16may be laptops, desktop computers, mobile devices such as tablets orso-called smart phones and the like. In some examples, the system 2includes at least one computing device having a first computing deviceand a second computing device 16, where the first computing device isconfigured to provide the comparative data from the first and secondsensors, and where the second computing device is configured to performone or more actions by outputting an alert, wherein the alert comprisesat least one of an audible alert, a visual alert, a haptic alert, a textalert, or a combination thereof. In some examples, the first computingdevice may be integrated in the personal protective equipment donned bythe worker, such as for example computing device 300 operably disposedin accessory 11, which can be operably disposed in the negative pressurereusable respirator. In some examples, the first computing devise 18 maybe a computing device 18 used by a worker in the work environment orremote from the work environment such that the worker can interact withthe system 2. In some embodiments, the first computing device 18 is acombination of these examples.

Workers 20, 24 interact with PPEMS 6 to control and actively manage manyaspects of safely equipment utilized by workers 10, such as accessingand viewing usage records, analytics and reporting. For example, workers20, 24 may review data acquired and stored by PPEMS 6, where the datamay include data specifying whether respiration occurred through atleast on valve, whether the respirator was donned, whether an initialseal check of the respirator was performed by the worker, starting andending times over a time duration (e.g., a day, a week, etc.), datacollected during particular events, such as pulling a respirator awayfrom the worker's face (e.g., such that the cavity formed by theworker's face and the respirator is not sealed, which may expose theworker to breathing hazards, without necessarily removing the respiratorfrom the worker 10), removal of a negative pressure reusable respirator13 from a worker 10, changes to operating parameters of a negativepressure reusable respirator 13, status changes to components ofnegative pressure reusable respirators 13 (e.g., a low battery event),motion of workers 10, detected impacts to negative pressure reusablerespirators 13 or hubs 14, sensed data acquired from the worker,environment data, and the like. In addition, workers 20, 24 may interactwith PPEMS 6 to perform asset tracking and to schedule maintenanceevents for individual pieces of safety equipment, e.g., negativepressure reusable respirators 13, to ensure compliance with anyprocedures or regulations. PPEMS 6 may allow workers 20, 24 to createand complete digital checklists with respect to the maintenanceprocedures and to synchronize any results of the procedures fromcomputing devices 16, 18 to PPEMS 6. In some examples, computing device16 is located within physical environment 8 where workers 10 and users20 are located. In some examples, computing device 16 is integral tonegative pressure reusable respirator 13 worn by worker 10. In someexamples, computing device 18 is located remote from physicalenvironment 8 where workers 10 and users 20 are located.

In some embodiments, PPEMS 6 may provide an integrated suite of personalsafety protection equipment management tools and implements varioustechniques of this disclosure. That is, in some examples, PPEMS 6provides an integrated, end-to-end system for managing personalprotection equipment, e.g., respirators, used by workers 10 within oneor more physical environments 8. These exemplary techniques may berealized within various parts of system 2.

PPEMS 6 may integrate an event processing platform configured to processthousand or even millions of concurrent streams of events from digitallyenabled devices, such as sensing stations 21, beacons 17, negativepressure reusable respirators 13, sensors on the negative pressurereusable respirators 13, and/or data hubs 14. An underlying analyticsengine of PPEMS 6 may apply models to the inbound streams to computeassertions, such as identified anomalies or predicted occurrences ofsafety events based on conditions or behavior patterns of workers 10.

Further, PPEMS 6 may provide real-time alerting and reporting to notifyworkers 10 and/or workers 20, 24 of any predicted events, anomalies,trends, and the like. The analytics engine of PPEMS 6 may, in someexamples, apply analytics to identify relationships or correlationsbetween sensed worker data, environmental conditions, geographic regionsand other factors and analyze the impact on safety events. PPEMS 6 maydetermine, based on the data acquired across populations of workers 10,which particular activities, possibly within certain geographic region,lead to, or are predicted to lead to, unusually high occurrences ofsafety events.

In this way, PPEMS 6 tightly integrates comprehensive tools for managingpersonal protective equipment with an underlying analytics engine andcommunication system to provide data acquisition, monitoring, activitylogging, reporting, behavior analytics and alert generation. Moreover,PPEMS 6 provides a communication system for operation and utilization byand between the various elements of system 2. Workers 20, 24 may accessPPEMS 6 to view results on any analytics performed by PPEMS 6 on dataacquired from workers 10. In some examples, PPEMS 6 may present aweb-based interface via a web server (e.g., an HTTP server) orclient-side applications may be deployed for devices of computingdevices 16, 18, 60, 300 used by workers 20, 24, such as desktopcomputers, laptop computers, mobile devices such as smartphones andtablets, accessories operably disposed on negative pressure reusablerespirators, or the like.

In some examples, PPEMS 6 may provide a database query engine fordirectly querying PPEMS 6 to view acquired safety data, compliance dataand any results of the analytic engine, e.g., by the way of dashboards,alert notifications, reports and the like. That is, workers 20, 24 orsoftware executing on computing devices 16, 18, 60, 300 may submitqueries to PPEMS 6 and receive data corresponding to the queries forpresentation in the form of one or more reports or dashboards. Suchdashboards may provide various insights regarding system 2, such asbaseline (“normal”) operation across worker populations, identificationsof any anomalous workers engaging in abnormal activities that maypotentially expose the worker to risks, identifications of anygeographic regions within environments 8 for which unusually anomalous(e.g., high) safety events have been or are predicted to occur,identifications of any of environments 8 exhibiting anomalousoccurrences of safety events relative to other environments, and thelike.

As illustrated in detail below, PPEMS 6 may simplify workflows forindividuals charged with monitoring and ensure safety compliance for anentity or environment. That is, PPEMS 6 may enable active safetymanagement and allow an organization to take preventative or correctionactions with respect to certain regions within environments 8,particular pieces of safety equipment or individual workers 10, defineand may further allow the entity to implement workflow procedures thatare data-driven by an underlying analytical engine.

As one example, the underlying analytical engine of PPEMS 6 may beconfigured to compute and present customer-defined metrics for workerpopulations within a given environment 8 or across multiple environmentsfor an organization as a whole. For example, PPEMS 6 may be configuredto acquire data and provide aggregated performance metrics and predictedbehavior analytics across a worker population (e.g., across workers 10of either or both of environments 8A, 8B). Furthermore, workers 20, 24may set benchmarks for occurrence of any safety incidences, and PPEMS 6may track actual performance metrics relative to the benchmarks forindividuals or defined worker populations.

As another example, PPEMS 6 may further trigger an alert if certaincombinations of conditions are present, e.g., to accelerate examinationor service of a safety equipment, such as one of negative pressurereusable respirators 13. In this manner, PPEMS 6 may identify individualnegative pressure reusable respirators 13 or workers 10 for which themetrics do not meet the benchmarks and prompt the workers to interveneand/or perform procedures to improve the metrics relative to thebenchmarks, thereby ensuring compliance and actively managing safety forworkers 10.

In accordance with techniques of this disclosure, PPEMS 6 determineswhether a contaminant capture device 23 of a negative pressure reusablerespirator 13 is due for replacement. In some examples, PPEMS 6determines whether a contaminant capture device (e.g., contaminantcapture device 23A) is due to be replaced based at least in part sensordata generated by two or more sensors in environment 8B, such as firstsensor data generated by first sensor on the negative pressure reusablerespirator 13 and second sensor data generated by second sensor negativepressure reusable respirator 13. In some examples, PPEMS 6 determineswhether negative pressure reusable respirator 13 was donned by a weareras well as determining whether a contaminant capture device (e.g.,contaminant capture device 23A) is due to be replaced, where suchdeterminations are based at least in part sensor data generated by twoor more sensors in environment 8B, such as first sensor data generatedby first sensor operably disposed on the negative pressure reusablerespirator 13 and second sensor data generated by second sensor operablydisposed on the negative pressure reusable respirator 13.

In some examples, contaminant capture device 23A includes a particulatefilter and negative pressure reusable respirator 13A includes a pressuresensor configured to detect the air pressure of air within a cavityformed and sealed by the face of worker 10A and negative pressurereusable respirator 13A. In such examples, PPEMS 6 determines whethercontaminant capture device 23A should be replaced based on the airpressure within the cavity sealed by the face of worker 10A and negativepressure reusable respirator 13A. For example, the air pressure sensordetects a decrease in the air pressure within the cavity as worker 10Ainhales. PPEMS 6 may determine a pressure differential as worker 10Ainhales overtime. In other words, PPEMS 6 may determine a baselinepressure within the sealed cavity when the worker inhales at a firsttime (e.g., when the filter is new), a current pressure within thesealed cavity when the worker inhales at a second, later time, anddetermine the pressure differential as a difference between the baselinepressure and the current pressure.

In some embodiments, PPEMS may additionally determine a baselineposition of at least one valve when the worker inhales at a first time(e.g. when the filter is new), a current valve position when the workerinhales at a second, later time, and compare the air pressure data andvalve position data at the first time and compare the air pressure dataand valve position data at the second time to determine whether thecontaminant capture device 23A should be replaced. For example, as thecontaminant capture device 23A increases air flow resistance due tofilter loading, the air pressure differential required to induce a givenvalve position may increase, indicating that the contaminant capturedevice 23A should be replaced.

In some embodiments, PPEMS may additionally determine a baselineposition of at least one valve and a baseline pressure when the workerinhales at a first time (e.g. when the filter is new), a current valveposition and a current pressure when the worker inhales at a second,later time, and compare the air pressure data and valve position data atthe first time and compare the air pressure data and valve position dataat the second time to determine whether the contaminant capture device23A should be replaced. For example, as the contaminant capture device23A increases air flow resistance due to filter loading, the airpressure differential required to induce a given valve position mayincrease, indicating that the contaminant capture device 23A should bereplaced.

PPEMS 6 may compare the pressure differential to a threshold decrease inair pressure (also referred to as a threshold pressure differential). Insome examples, PPEMS 6 may determine that contaminant capture device 23Ais due for replacement in response to determining that the pressuredifferential satisfies (e.g., is greater than or equal to) a thresholdpressure differential. PPEMS 6 may determine that contaminant capturedevice 23A is not due for replacement in response to determining thatthe pressure differential does not satisfy a threshold pressuredifferential.

In some examples, contaminant capture device 23A includes a chemicalcartridge and environment 8B includes a sensing station 21A configuredto detect the concentration of one or more contaminants (e.g., gases orvapors) in work environment 8B. In such examples, PPEMS 6 may determinewhether contaminant capture device 23A should be replaced based at leastin part on the concentration of the contaminant and an amount of timeworker 10A is located with environment 8B. For example, PPEMS 6 maydetermine a threshold protection time (e.g., an amount of time thatcontaminant capture device 23A protects worker 10A) based on device datafor the contaminant capture device 23A and the contaminationconcentration. The device data may indicate a type of contaminantcapture device 23A, an amount of contaminants the contaminant capturedevice 23A can capture (also referred to as a contaminant capturecapacity), among others. For instance, PPEMS 6 may determine thethreshold protection time based on the contaminant capture capacity ofcontaminant capture device 23A and the contaminant concentration withinwork environment 8B. In such instances, PPEMS 6 determines whether theactual usage time (e.g., time within environment 8B) of contaminantcapture device 23A satisfies the threshold protection time. In someexamples, PPEMS 6 determines that contaminant capture device 23A is notdue for replacement in response to determining that the actual usagetime of contaminant capture device 23A does not satisfy (e.g., is lessthan) the threshold protection time. As another example, PPEMS 6determines that contaminant capture device 23A is due for replacement inresponse to determining that the actual usage time of contaminantcapture device 23A satisfies (e.g., is greater than or equal to) thethreshold protection time.

Responsive to determining that contaminant capture device 23A is due forreplacement, PPEMS 6 performs one or more actions. In one example, PPEMS6 outputs a notification to computing device associated with worker 10A(e.g., hub 14A), computing devices 16, 18, 60, 300 associated withworkers 20, 24, to safety stations 15, or other computing devices. Insome examples, the notification includes data indicating the negativepressure reusable respirator 13A or component of the negative pressurereusable respirator 13A that is due for replacement, the workerassociated with the respirator, a location of the worker, among otherdata. In some instances, a computing device (e.g., hub 14A) receives thenotification and output an alert, for instance, by outputting anaudible, visual, or tactile alert.

In some examples, PPEMS 6 determines whether the negative pressurereusable respirator provides a seal around the worker's face. PPEMS 6may determine whether the negative pressure reusable respirator 13Aprovides a seal based on sensor data from an infrared sensor of negativepressure reusable respirator 13A. For instance, the infrared sensor maygenerate data indicative of a distance between a negative pressurereusable respirator 13A (e.g., a face piece of negative pressurereusable respirator 13A) and the face of worker 10A. In some examples,PPEMS 6 determines whether negative pressure reusable respirator 13Aseals a cavity between the worker's face and the respirator based on thedistance between the negative pressure reusable respirator and the faceof the worker. For example, PPEMS 6 may compare the distance to athreshold distance. In some instances, PPEMS 6 determines that negativepressure reusable respirator 13A does not provide a seal in response todetermining that the distance satisfies (e.g., is greater than) athreshold distance. For instance, PPEMS 6 may determine that worker 10Ais not clean shaven or pulled respirator 13A away from his or her facein response to determining that the distance satisfies (e.g., is greaterthan) a threshold distance. In such instances, PPEMS 6 may output anotification to another computing device (e.g., computing devices 18)indicating worker 10A is not clean shaven or pulled respirator 13A awayfrom his or her face. In some instances, PPEMS 6 causes a computingdevice associated with worker 10A (e.g., hub 14A) to output an alert(e.g., visual, audible, haptic) indicating negative pressure reusablerespirator 13A does not provide a seal around the worker's face. In someexamples, the alert indicates worker 10A is not clean shaven or pulledrespirator 13A away from his or her face. In this way, PPEMS 6 mayprovide real-time (or near real-time) monitoring of the negativepressure reusable respirator, which may increase worker safety byalerting workers 10 when the respective negative pressure reusablerespirators 13 do not form a seal with the face of the respectiveworkers 10 and thus potentially expose the respective worker 10 tohazards within the air present in the work environment (e.g., within airexterior to the respirator).

In some examples, each contaminant capture device 23 includes acommunication unit that is configured to transmit information indicativeof the respective contaminant capture device 23 to a computing system.For example, the communication device may include an RFID tag configuredto output identification information (e.g., a unique identifier, a typeof contaminant capture device, etc.) for the respective contaminantcapture device 23. In some instances, PPEMS 6 determines whethercontaminant capture device 23A is configured to protect worker 10A fromhazards within the work environment 8B based on the identificationinformation. For instance, PPEMS 6 may determine the types ofcontaminants that contaminant capture device 23A is configured toprotect against based on a type of the contaminant capture device 23Aand compare such types of contaminants to types of contaminants withinthe work environment 8B. In some examples, the PPEMS 6 alerts worker 10Awhen the contaminant capture device 23A is not configured to protectworkers from contaminants within the work environment 8B, which mayenable a worker to utilize the correct contaminant capture device forthe hazards within the environment, thereby potentially increasingworker safety.

While described with reference to PPEMS 6, the functionality describedin this disclosure may be performed by other computing devices, such asone or more hubs 14 or computing devices 16, 18, 60, 300 of one or morenegative pressure reusable respirators 13. For example, one or morecomputing devices 16, 18, 60, 300 may determine whether a contaminantcapture device 23 of a negative pressure reusable respirator 13 is duefor replacement. As another example, computing devices 16, 18, 60, 300may determine whether negative pressure reusable respirator 13A providesa seal between the face of worker 10A and negative pressure reusablerespirator 13A. In yet another example, computing devices 16, 18, 60,300 determines whether contaminant capture device 23A is configured toprotect worker 10A from contaminants within the work environment 8B. Insome examples, multiple computing devices (e.g., computing devices 16,18, 60, 300) may collectively perform the functionality described inthis disclosure. For example, PPEMS 6 may determine a thresholdprotection time associated with a contaminant capture device (e.g., achemical cartridge) and one or more computing devices 16, 18, 60, 300may determine whether the actual usage time for the contaminant capturedevice satisfies the threshold protection time.

In this way, techniques of this disclosure may enable a computing systemto more accurately or timely determine whether a contaminant capturedevice 23 is due for replacement. The computing system may notify (e.g.,in real-time) workers when a contaminant capture device is due forreplacement, which may enable a worker to replace the contaminantcapture device. Replacing the contaminant capture device in a moretimely manner may increase worker safety. For example, replacing acontaminant capture device (e.g., a particulate filter and/or chemicalcartridge) of a respirator in a more timely manner may protect theworker by preventing gases from breaking through a chemical cartridgeand/or improving the ability of the worker to breathe when using aparticulate filter while still protecting the worker from particulates.

FIG. 7 is a block diagram providing an operating perspective of PPEMS 6when hosted as cloud-based platform capable of supporting multiple,distinct environments 8 having an overall population of workers 10, inaccordance with techniques described herein. In the example of FIG. 6,the components of PPEMS 6 are arranged according to multiple logicallayers that implement the techniques of the disclosure. Each layer maybe implemented by one or more modules comprised of hardware, software,or a combination of hardware and software.

In FIG. 7, safety equipment 62 include personal protective equipment(PPEs) (such as, for example negative pressure reusable respirators 13),beacons 17, and sensing stations 21. In some embodiments, negativepressure reusable respirators include at least one accessory 11 havingcomputing device 300 (as shown in FIG. 7) operably disposed thereon. Insome embodiments, computing device 300 operably disposed on accessory 11is used alone or in combination with computing device 60.

Safety equipment 62, HUBs 14, safety stations 15, as well as computingdevices 60, 300, operate as clients 63 that communicate with PPEMS 6 viainterface layer 64. Computing devices 60, 300 typically execute clientsoftware applications, such as desktop applications, mobileapplications, and web applications. Computing devices 60 may representany of computing devices 16, 18 of FIG. 5, 60 of FIG. 7 and 300 of FIG.8. Examples of computing devices 16, 18, 60, 300 may include a portableor mobile computing device (e.g., accessory 11, smartphone, wearablecomputing device, tablet), laptop computers, desktop computers, smarttelevision platforms, and servers, to name only a few examples.

Client applications executing on computing devices 16, 18, 60, 300 maycommunicate with PPEMS 6 to send and receive data that is retrieved,stored, generated, and/or otherwise processed by services 68. Forinstance, the client applications may request and edit safety event dataincluding analytical data stored at and/or managed by PPEMS 6. In someexamples, client applications may request and display aggregate safetyevent data that summarizes or otherwise aggregates numerous individualinstances of safety events and corresponding data obtained from safetyequipment 62 and/or generated by PPEMS 6. The client applications mayinteract with PPEMS 6 to query for analytics data about past andpredicted safety events, behavior trends of workers 10, to name only afew examples. In some examples, the client applications may output fordisplay data received from PPEMS 6 to visualize such data for workers ofclients 63. As further illustrated and described in below, PPEMS 6 mayprovide data to the client applications, which the client applicationsoutput for display in worker interfaces.

Client applications executing on computing devices 16, 18, 60, 300 maybe implemented for different platforms but include similar or the samefunctionality. For instance, a client application may be a desktopapplication compiled to run on a desktop operating system or a mobileapplication compiled to run on a mobile operating system. As anotherexample, a client application may be a web application such as a webbrowser that displays web pages received from PPEMS 6. In the example ofa web application, PPEMS 6 may receive requests from the web application(e.g., the web browser), process the requests, and send one or moreresponses back to the web application. In this way, the collection ofweb pages, the client-side processing web application, and theserver-side processing performed by PPEMS 6 collectively provides thefunctionality to perform techniques of this disclosure. In this way,client applications use various services of PPEMS 6 in accordance withtechniques of this disclosure, and the applications may operate withinvarious different computing environment (e.g., embedded circuitry orprocessor of a PPE, a desktop operating system, mobile operating system,or web browser, to name only a few examples).

As shown in FIG. 7, PPEMS 6 includes an interface layer 64 thatrepresents a set of application programming interfaces (API) or protocolinterface presented and supported by PPEMS 6. Interface layer 64initially receives messages from any of clients 63 for furtherprocessing at PPEMS 6. Interface layer 64 may therefore provide one ormore interfaces that are available to client applications executing onclients 63. In some examples, the interfaces may be applicationprogramming interfaces (APIs) that are accessible over a network.Interface layer 64 may be implemented with one or more web servers. Theone or more web servers may receive incoming requests, process and/orforward data from the requests to services 68, and provide one or moreresponses, based on data received from services 68, to the clientapplication that initially sent the request. In some examples, the oneor more web servers that implement interface layer 64 may include aruntime environment to deploy program logic that provides the one ormore interfaces. As further described below, each service may provide agroup of one or more interfaces that are accessible via interface layer64.

In some examples, interface layer 64 may provide Representational StateTransfer (RESTful) interfaces that use HTTP methods to interact withservices and manipulate resources of PPEMS 6. In such examples, services68 may generate JavaScript Object Notation (JSON) messages thatinterface layer 64 sends back to the client application 61 thatsubmitted the initial request. In some examples, interface layer 64provides web services using Simple Object Access Protocol (SOAP) toprocess requests from client applications 61. In still other examples,interface layer 64 may use Remote Procedure Calls (RPC) to processrequests from clients 63. Upon receiving a request from a clientapplication to use one or more services 68, interface layer 64 sends thedata to application layer 66, which includes services 68.

As shown in FIG. 7, PPEMS 6 also includes an application layer 66 thatrepresents a collection of services for implementing much of theunderlying operations of PPEMS 6. Application layer 66 receives dataincluded in requests received from client applications 61 and furtherprocesses the data according to one or more of services 68 invoked bythe requests. Application layer 66 may be implemented as one or morediscrete software services executing on one or more application servers,e.g., physical or virtual machines. That is, the application serversprovide runtime environments for execution of services 68. In someexamples, the functionality interface layer 64 as described above andthe functionality of application layer 66 may be implemented at the sameserver.

Application layer 66 may include one or more separate software services68, e.g., processes that communicate, e.g., via a logical service bus 70as one example. Service bus 70 generally represents logicalinterconnections or set of interfaces that allows different services tosend messages to other services, such as by a publish/subscriptioncommunication model. For instance, each of services 68 may subscribe tospecific types of messages based on criteria set for the respectiveservice. When a service publishes a message of a particular type onservice bus 70, other services that subscribe to messages of that typewill receive the message. In this way, each of services 68 maycommunicate data to one another. As another example, services 68 maycommunicate in point-to-point fashion using sockets or othercommunication mechanisms. Before describing the functionality of each ofservices 68, the layers are briefly described herein.

Data layer 72 of PPEMS 6 represents a data repository that providespersistence for data in PPEMS 6 using one or more data repositories 74.A data repository, generally, may be any data structure or software thatstores and/or manages data. Examples of data repositories include butare not limited to relational databases, multi-dimensional databases,maps, and hash tables, to name only a few examples. Data layer 72 may beimplemented using Relational Database Management System (RDBMS) softwareto manage data in data repositories 74. The RDBMS software may manageone or more data repositories 74, which may be accessed using StructuredQuery Language (SQL). Data in the one or more databases may be stored,retrieved, and modified using the RDBMS software. In some examples, datalayer 72 may be implemented using an Object Database Management System(ODBMS), Online Analytical Processing (OLAP) database or other suitabledata management system.

As shown in FIG. 7, each of services 68A-68G (collectively, services 68)is implemented in a modular form within PPEMS 6. Although shown asseparate modules for each service, in some examples the functionality oftwo or more services may be combined into a single module or component.Each of services 68 may be implemented in software, hardware, or acombination of hardware and software. Moreover, services 68 may beimplemented as standalone devices, separate virtual machines orcontainers, processes, threads or software instructions generally forexecution on one or more physical processors. In some examples, one ormore of services 68 may each provide one or more interfaces that areexposed through interface layer 64. Accordingly, client applications ofcomputing devices 16, 18, 60, 300 may call one or more interfaces of oneor more of services 68 to perform techniques of this disclosure.

In accordance with techniques of the disclosure, services 68 may includean event processing platform including an event endpoint frontend 68A,event selector 68B, event processor 68C, high priority (HP) eventprocessor 68D, notification service 68E, and analytics service 68F.

Event endpoint frontend 68A operates as a frontend interface forexchanging communications with hubs 14, safety stations 15, and safetyequipment 62. In other words, event endpoint frontend 68A operates to asa frontline interface to safety equipment deployed within environments 8and utilized by workers 10. In some instances, event endpoint frontend68A may be implemented as a plurality of tasks or jobs spawned toreceive individual inbound communications of event streams 69 thatinclude data sensed and captured by the safety equipment 62. Forinstance, event streams 69 may include sensor data, such as first andsecond sensor data, from one or more negative pressure reusablerespirators 13 and environmental data from one or more sensing stations21. When receiving event streams 69, for example, event endpointfrontend 68A may spawn tasks to quickly enqueue an inboundcommunication, referred to as an event, and close the communicationsession, thereby providing high-speed processing and scalability. Eachincoming communication may, for example, carry data recently captureddata representing sensed conditions, motions, temperatures, actions orother data, generally referred to as events. Communications exchangedbetween the event endpoint frontend 68A and safety equipment 62 and/orhubs 14 may be real-time or pseudo real-time depending on communicationdelays and continuity.

Event selector 68B operates on the stream of events 69 received fromsafety equipment 62 and/or hubs 14 via frontend 68A and determines,based on rules or classifications, priorities associated with theincoming events. For example, safety rules may indicate that incidentsof incorrect equipment for a given environment, incorrect usage of PPEs,or lack of sensor data associated with a worker's vital signs are to betreated as high priority events. Based on the priorities, event selector68B enqueues the events for subsequent processing by event processor 68Cor high priority (HP) event processor 68D. Additional computationalresources and objects may be dedicated to HP event processor 68D so asto ensure responsiveness to critical events, such as incorrect usage ofPPEs, lack of vital signs, and the like. Responsive to processing highpriority events, HP event processor 68D may immediately invokenotification service 68E to generate alerts, instructions, warnings orother similar messages to be output to safety equipment 62, hubs 14, ordevices used by workers 20, 24. Events not classified as high priorityare consumed and processed by event processor 68C.

In general, event processor 68C or high priority (HP) event processor68D operate on the incoming streams of events to update event data 74Awithin data repositories 74. In general, event data 74A may include allor a subset of data generated by safety equipment 62. For example, insome instances, event data 74A may include entire streams of dataobtained from negative pressure reusable respirator 13, sensing stations21, etc. In other instances, event data 74A may include a subset of suchdata, e.g., associated with a particular time period.

Event processors 68C, 68D may create, read, update, and delete eventdata stored in event data 74A. Event data for may be stored in arespective database record as a structure that includes name/value pairsof data, such as data tables specified in row/column format. Forinstance, a name (e.g., column) may be “workerID” and a value may be anemployee identification number. An event record may include data suchas, but not limited to: worker identification, acquisition timestamp(s)and sensor data. For example, event stream 69 for one or more sensorsassociated with a given worker (e.g., worker 10A) may be formatted asfollows:

{“eventTime”:“2015-12-31T18:20:53.1210933Z”,“workerID”:“00123”,

“RespiratorType”:“Model 600”, “ContaminantCaptureDeviceType”:“P90X”,“AirPressurePSI”: 14.0}.

In some examples, event stream 69 include category identifiers (e.g.,“eventTime”, “workerID”, “RespiratorType”,“ContaminantCaptureDeviceType”, and “AirPressurePSI”), as well ascorresponding values for each category.

In some examples, analytics service 68F is configured to perform indepth processing of the incoming stream of events to perform real-timeanalytics. In this way, stream analytic service 68F may be configured todetect anomalies, transform incoming event data values, trigger alertsupon detecting safety concerns based on conditions or worker behaviors.In addition, stream analytic service 68F may generate output forcommunicating to safety equipment 62, safety stations 15, hubs 14, orcomputing devices 16, 18, 60, 300. In some embodiments, analyticsservice 68F is configured to operate as part of PPEMS, which can beoperated by accessory 11 operably disposed on negative pressure reusablerespirator 13.

Record management and reporting service (RMRS) 68G processes andresponds to messages and queries received from computing devices 60 viainterface layer 64. For example, record management and reporting service68G may receive requests from client computing devices for event datarelated to individual workers, populations or sample sets of workers,geographic regions of environments 8 or environments 8 as a whole,individual or groups (e.g., types) of safety equipment 62. In response,record management and reporting service 68G accesses event informationbased on the request. Upon retrieving the event data, record managementand reporting service 68G constructs an output response to the clientapplication that initially requested the information. In some examples,the data may be included in a document, such as an HTML document, or thedata may be encoded in a JSON format or presented by a dashboardapplication executing on the requesting client computing device. Forinstance, as further described in this disclosure, example workerinterfaces that include the event information are depicted in thefigures.

As additional examples, record management and reporting service 68G mayreceive requests to find, analyze, and correlate PPE event information.For instance, record management and reporting service 68G may receive aquery request from a client application for event data 74A over ahistorical time frame, such as a worker can view PPE event informationover a period of time and/or a computing device can analyze the PPEevent information over the period of time.

In accordance with techniques of this disclosure, in some examples,analytics service 68F determines whether a contaminant capture device 23of a negative pressure reusable respirator 13 is due for replacement. Inone example, analytics service 68F determines whether a contaminantcapture device 23A of negative pressure reusable respirator 13A of FIG.5 is due for replacement based at least in part on sensor data (e.g.,environmental sensor data and/or air pressure sensor data) and one ormore rules. In some examples, the one or more rules are stored in models74B. Although other technologies can be used, in some examples, the oneor more rules are generated using machine learning. In other words, inone example implementation, analytics service 68F utilizes machinelearning when operating on event streams 69 so as to perform real-timeanalytics. That is, analytics service 68F may include executable codegenerated by application of machine learning. The executable code maytake the form of software instructions or rule sets and is generallyreferred to as a model that can subsequently be applied to event streams69.

Example machine learning techniques that may be employed to generatemodels 74B can include various learning styles, such as supervisedlearning, unsupervised learning, and semi-supervised learning. Exampletypes of algorithms include Bayesian algorithms, Clustering algorithms,decision-tree algorithms, regularization algorithms, regressionalgorithms, instance-based algorithms, artificial neural networkalgorithms, deep learning algorithms, dimensionality reductionalgorithms and the like. Various examples of specific algorithms includeBayesian Linear Regression, Boosted Decision Tree Regression, and NeuralNetwork Regression, Back Propagation Neural Networks, the Apriorialgorithm, K-Means Clustering, k-Nearest Neighbor (kNN), Learning VectorQuantization (LVQ), Self-Organizing Map (SOM), Locally Weighted Learning(LWL), Ridge Regression, Least Absolute Shrinkage and Selection Operator(LASSO), Elastic Net, and Least-Angle Regression (LARS), PrincipalComponent Analysis (PCA) and Principal Component Regression (PCR).

Analytics service 68F generates, in some example, separate models forindividual workers, a population of workers, a particular environment, atype of respirator, a type of contaminant capture device, orcombinations thereof. Analytics service 68F may update the models basedon sensor data generated by PPE sensors or environmental sensors. Forexample, analytics service 68F may update the models for individualworkers, a population of workers, a particular environment, a type ofrespirator, a type of contaminant capture device, or combinationsthereof based on data received from safety equipment 62.

In some examples, analytics service 68F applies one or more of models74B to event data 74A to determine whether contaminant capture device23A of negative pressure reusable respirator 13A is due for replacement.In some examples, analytics service 68F applies one or more models 74Bto sensor data received from negative pressure reusable respirator 13 todetermine whether a contaminant capture device 23 is due forreplacement. In one example, contaminant capture device 23A ofrespirator 13A includes a particulate filter and analytics service 68Freceives sensor data (e.g., pressure data) from a pressure sensor thatmeasures a gas characteristic, such as the air pressure of the air,within a cavity formed by the worker's face and respirator 13A. In someexamples, analytics service 68F applies a model from models 74B to theair pressure data from the pressure sensor. For example, analyticsservice 68F may receive pressure data indicating a pressure differentialin the air pressure within the cavity over time as the worker inhales,and may determine whether the particulate filter is due for replacementbased on the air pressure differential.

In some examples, computing device 300 (shown in FIG. 8) is furtherconfigured to apply a model 322 to the first sensor data and the secondsensor data to determine whether respiration occurred through the atleast one valve and a wearer seal check was, performed, was notperformed, was performed such that seal check met a certain qualitystandard, and combinations thereof. In some examples, analytics service68F (shown in FIG. 7) applies a model from models 74B to the firstsensor data and the second sensor data to determine whether respirationoccurred through the at least one valve and a wearer seal check wasperformed, was not performed, was performed such that seal check met acertain quality standard, and combinations thereof. In some examples,model 74B of PPEMS 6 (shown in FIG. 7) or model 322 of computing device300 (shown in FIG. 8) is trained based at least in part on first sensordata and second sensor data associated with one or more of the wearer, aplurality of additional wearers, contaminants within an environmentaround the wearer, a notification from another computing device, a typeof contaminant capture device, or combinations thereof. In someembodiments, models useful in the present disclosure are time dependent.

In some examples, referring again to FIGS. 1 and 2, analytics service68F may determine whether contaminant capture device 23A is due forreplacement based on valve position data and gas characteristic data,such as pressure data. For example, analytics service 68F may apply oneor more models of models 74B to negative pressure reusable respiratorpressure sensor data and valve position sensor data. Typically, airpressure within the cavity formed between the worker's face and negativepressure reusable respirator decreases as the worker inhales.Additionally, the valve position may change as the worker inhales, dueto the pressure differential within the negative pressure reusablerespirator. For example, analytics service 68F may determine a pressuredifferential over time for the pressure when worker 10A inhales, andvalve position data over the same time period. When contaminant capturedevice 23 is new, the pressure differential required to induce arelative change in valve position may be relatively small, compared tothe pressure differential required to induce a relative change in valveposition when contaminant capture device 23 is relatively saturated withparticulates. For instance, when contaminant capture device 23 isrelatively saturated, a greater pressure differential may be required toinduce a relative change in valve position than when contaminant capturedevice 23 is new, due to the increased air flow resistance ofcontaminant capture device 23 relative to the valve.

In some examples, the sensor data received from safety equipment 62includes physiological sensor data generated by one or morephysiological sensors associated with a worker 10. Analytics service 68Fmay determine whether contaminant capture device 23A is due forreplacement based on physiological data and pressure data. For example,analytics service 68F may apply one or more models of models 74B to PPEpressure sensor data and physiological sensor data. Typically, the airpressure within the cavity formed between the worker's face andrespirator decreases as the worker inhales. For example, analyticsservice 68F may determine a pressure differential over time for thepressure when worker 10A inhales. When the particulate filter is new andthe worker is not breathing heavily, the pressure differential may berelatively small, compared to the pressure differential when theparticulate filter is relatively saturated with particulates. Forinstance, when the particulate filter is relatively saturated, worker10A may breathe hard such that the pressure may decrease more than whenthe particulate filter is relatively new.

In some examples, analytics service 68F applies one or more models to atleast the pressure data to determine whether the particulate filter isdue for replacement. Models 74B may be trained based on pressuredifferentials for a particular worker, worker feedback indicating worker10A is having difficulty breathing, a type of respirator, a type ofparticulate filter, a type of contaminant, or a combination therein. Insome examples, the one or more models 74B are trained based onphysiological data (e.g., heart rate data, breathing rate data). Forexample, a worker may breathe heavy (e.g., thus increasing the airpressure differential) because a filter is saturated (e.g., and due forreplacement) or because a worker is physically active (e.g., movingwithin the environment, such as walking up stairs). In such examples,analytics service 68F applies one or more of models 74B to the PPE airpressure data and the physiological data to determine whether theparticulate filter is saturated (e.g., such that the particulate filteris due for replacement). For example, analytics service 68F apply themodels 74B to air pressure data indicating a relatively high pressuredifferential and physiological sensor data indicating a relatively highbreathing rate and/or relatively high pulse rate, and determine based onapplication of the model 74B that the particulate filter is not due forreplacement. In other words, analytics service 68G may infer that theworker is breathing hard because he or she is exercising rather than dueto a saturated or congested particulate filter, such that analyticsservice 68F may determine that particulate filter is not due forreplacement. As another example, analytics service 68F applies themodels 74B to air pressure data indicating a relatively high pressuredifferential and physiological sensor data indicating a relatively lowbreathing rate and/or relatively low pulse rate, and determine based onapplication of the model 74B that the particulate filter is due forreplacement.

In some examples, contaminant capture device 23B of negative pressurereusable respirator 13B includes a chemical cartridge and analyticsservice 68F determines whether the contaminant capture device 23B is duefor replacement based at least in part on sensor data from one or moresensing stations 21. In one example, the sensor data includes dataindicative the concentration level of one or more respective gases,vapor, or other chemicals present in the air of environment 8B of FIG.5. Analytics service 68F applies one or more models 74B to theenvironmental sensor data generated by sensing stations 21 to determinewhether contaminant capture device 23B is due for replacement. Forinstance, analytics service 68F may determine, based on application ofone or more models 74B to the environmental sensor data, a thresholdexposure time (e.g., a maximum amount of time) that contaminant capturedevice 23B provides protection. In some examples, analytics service 68Fmay determine an amount of time worker 10B is located within environment8B, and compare the amount of time worker 10B is located withinenvironment 8B to the threshold exposure time to determine whethercontaminant capture device 23B is due for replacement. In some examples,hub 14A detects that worker 10A has entered environment 8B (e.g., basedon GPS) and sends data indicating that worker 10A has enteredenvironment 8B to PPEMS 6, such that analytics service 68F receivesevent data 74A (e.g., from hub 14) indicating worker 10A has enteredenvironment 8B and tracks the time worker 10A is located withinenvironment 8B.

In some examples, analytics service 68F dynamically determines an amountof contaminant capture device 23B (e.g., a chemical cartridge) that hasbeen consumed. For example, analytics service 68F may apply one or moremodels 74B to environmental sensor data from sensing stations 21continuously or periodically to determine the amount of contaminantcapture device 23B consumed as conditions of environment 8B changethroughout the day. In some instances, analytics service 68F determinesthat the concentration levels of a particular gas in environment 8B arerelatively high and that a relatively high proportion (e.g., 40%) ofcontaminant capture device 23B has been exhausted or consumed whileworker 10B utilized contaminant capture device 23B for a first period oftime (e.g., two hours). In another instance, analytics service 68F maydetermine that the concentration levels of the particular gas decreaseto a relatively low concentration (e.g., relative to the earlier periodof time) and that a relatively low (e.g., 20%) of contaminant capturedevice 23B was exhausted or consumed in the second period of time. Inone instance, analytics service 68F determines a cumulative amount ofcontaminant capture device 23B that has been consumed during the firstand second periods of time. In some examples, analytics service 68Fdetermines whether contaminant capture device 23B is due for replacementby comparing the cumulative consumption to a threshold consumption. Asone example, analytics service 68F determines that contaminant capturedevice 23B is due for replacement in response to determining that thecumulative consumption satisfies (e.g., is greater than) the thresholdconsumption or that contaminant capture device 23B is not due forreplacement in response to determining that the cumulative consumptiondoes not satisfy (e.g., is less than) the threshold consumption.

As described above, analytics service 68F determines, in one example,whether contaminant capture device 23B is due for replacement based onapplying one or more models 74B to at least a portion of event data 74A.Models 74B may be trained based on event data 74A associated with aparticular worker, a plurality of workers, the particular contaminantswithin the work environment 8B, a type of contaminant capture device 23utilized by the worker, or a combination therein. In some instances, theparticular models 74B applied to the event data 74A for worker 10A aretrained based on event data 74A for workers 10A and the models 74Bapplied to event data 74A for worker 10B are trained based on event data74A for worker 10B. In one example, the particular models 74B applied tothe event data 74A for worker 10A are trained based on event data 74Afor a plurality of workers 10. In some examples, the particular models74B applied to the event data 74A for worker 10A are trained based onthe type of contaminant capture device 23A utilized by worker 10A. Asyet another example, the particular models 74B applied to the event data74A for worker 10A may be trained based on contaminants within workenvironment 8B, while the particular models 74B applied to the eventdata 74A for a worker within environment 8A may be trained based oncontaminants within work environment 8A.

PPEMS 6 performs one or more actions in response to determining thatcontaminant capture device 23 is due for replacement. In some examples,notification service 68E outputs a notification indicating that acontaminant capture device 23 is due for replacement. For example,notification service 68E may output the notification to at least one ofclients 63 (e.g., one or more of computing devices 60, hubs 14, safetystations 15, or a combination therein). In one instance, thenotification indicates which worker of workers 10 is associated with thearticle or component that is due for replacement, a location of theworker, a location at which a replacement is located, etc. As anotherexample, notification service 68E may output a command (e.g., to arespective hub 14A or other computing device associated with worker 10A,such as a computing device 300 illustrated in FIG. 8) to output an alertindicating contaminant capture device 23A is due for replacement. Forexample, respirator hub 14A may receive the command and may output analert (e.g., visual, audible, haptic) to indicate contaminant capturedevice 23A is due for replacement. While PPEMS 6 is described asdetermining whether contaminant capture device 23 is due for replacementand performing actions, a computing device (e.g., a hub 14 or computingdevice of negative pressure reusable respirator 13) associated with aworker may perform similar functionality.

In some examples, analytics service 68F determines, based on event data74A, whether a contaminant capture device 23 of the negative pressurereusable respirator 13 satisfies one or more safety rules (e.g., for atask to be performed, for the hazards present or likely to be presentwithin work environment 8B). For example, analytics service 68F maydetermine whether one or more contaminant capture devices 23 utilized bya worker 10 (e.g., contaminant capture devices 23A utilized by worker10A) satisfies one or more safety rules associated with work environment8B. In some instances, models 74B include safety rules specifying a typeof contaminant capture device 23 associated with each of workenvironments 8B or associated with particular hazards (e.g., gases,vapors, particulates). In such instances, analytics service 68Fdetermines whether contaminant capture devices 23A satisfies the safetyrules based on data received from the contaminant capture device 23A.For instance, each identification information corresponding to thecontaminant capture device 23A (e.g., information identifying a type ofthe contaminant capture device 23A) and a communication device, such asan RFID tag (e.g., passive RFID tag), that transmits the information. Inone instance, the memory device includes an RFID tag that storesidentification information for contaminant capture device 23A. Inanother instance, contaminant capture device 23A includes an identifierindicative of identification information for contaminant capture device23A.

In some examples, negative pressure reusable respirator 13A includes acomputing device (e.g., located between the facepiece and the worker'scontaminant capture device 23 may include a memory device that storesinformation) that includes a communication device (e.g., a RFID reader)configured to receive information from a contaminant capture device 23A.In one example, negative pressure reusable respirator 13A includes acomputing device that receives the identification information fromnegative pressure reusable respirator 13A and outputs the identificationinformation to PPEMS 6. PPEMS 6 may receive the identificationinformation (e.g., indicating a type of contaminant capture device 23A),determine one or more rules associated with contaminant capture device23A, and determine whether the type of the contaminant capture device23A satisfies the rules. In one instance, analytics service 68Fdetermines whether the type of contaminant capture device 23A is thecorrect type of contaminant capture device 23A for the environment orhazards within the environment. As another example, a computing deviceassociated with worker 10A (e.g., hub 14A or a computing device 16, 18,60 and 300) may determine whether contaminant capture device 23Asatisfies the one or more safety rules.

In accordance with one or more aspects of this disclosure, in someexamples, analytics service 68F determines whether usage of one or morenegative pressure reusable respirators 13 satisfies one or more safetyrules associated with a worker. In one example, analytics service 68Fdetermines whether usage of negative pressure reusable respirator 13A byworker 10A satisfies a safety rule based at least in part on worker data74C, models 74B, event data 74A (e.g., sensor data), or a combinationtherein. The safety rules may be associated with conditions indicatingwhether a worker is clean shaven or lifts a respirator from his or herface.

In some examples, analytics service 68F determines whether usage ofnegative pressure reusable respirator 13A satisfies a safety rule bycomparing a distance between negative pressure reusable respirator 13Aand a face of worker 10A to a threshold distance. Analytics service 68Fdetermine the distance between negative pressure reusable respirator 13Aand a face of worker 10A based on sensor data. In one instance, eventdata 74A for worker 10A includes sensor data indicative of the distance(e.g., actual distance) between the face of worker 10A and negativepressure reusable respirator 13A. For instance, the event data 74A mayinclude data generated by an infrared sensor of a computing device ofnegative pressure reusable respirator 13A. In some examples, analyticsservice 68F determines that the distance between the face of worker 10Aand negative pressure reusable respirator 13A satisfies (e.g., isgreater than or equal to) a threshold distance, which may indicate thatworker 10A has lifted negative pressure reusable respirator 13A awayfrom his or her face, that worker 10A has facial hair (e.g., is notclean shaven), that negative pressure reusable respirator 13A is notpositioned properly upon the face of worker 10A, that worker 10A has notcompleted a wearer seal check that satisfies a least one threshold,information about the physical state of a negative pressure reusablerespirator 13A, or usage information about a negative pressure reusablerespirator 13A.

In some examples, the threshold distance may be associated with a groupof workers 10. For example, analytics service 68F may utilize a singlethreshold distance for each of workers 10. In some examples, each workerof workers 10A may be associated with a respective threshold distance(e.g., stored in worker data 74C or safety rules 74B). For example, toensure the space between the face of worker 10A and negative pressurereusable respirator 13A remains sealed from contaminated air within workenvironment 8B, worker 10A may be required to be clean shaven. Worker10A may be clean shaven when at least a threshold amount of facial hair(e.g., 80%, 90%, 95%, etc.) is removed from portions of worker 10A'sface that are capable of growing facial hair. In such examples, thethreshold distance associated with each respective worker of workers 10may correspond to respective distance between the face of the worker anda respirator when the worker is known to be clean shaven. In otherwords, the threshold distance for worker 10A may be different than thethreshold distance for worker 10B. In one example, analytics service 68Fdetermines that the usage of negative pressure reusable respirator 13Asatisfies a safety rule by determining that the distance between theface of worker 10A and negative pressure reusable respirator 13Asatisfies (e.g., is greater than) the threshold distance associated withworker 10A. As another example, analytics service 68F may determine thatthe usage of negative pressure reusable respirator 13B does not satisfythe safety rule by determining that the distance between the face ofworker 10B and negative pressure reusable respirator 13B does notsatisfy (e.g., is less than) the threshold distance associated withworker 10B.

According to some examples, analytics service 68F may determine whetherthe distance between the face of worker 10A and negative pressurereusable respirator 13A satisfies different threshold distances. Forexample, a first threshold distance may be associated with the presenceof facial hair and a second threshold distance (e.g., greater than thefirst threshold distance) may be lifting or removing the negativepressure reusable respirator 13. In some examples, analytics service 68Fmay determine that worker 10A has facial hair (e.g., is not cleanshaven) in response to determining that the distance between the face ofworker 10A and negative pressure reusable respirator 13A satisfies afirst threshold distance, and that worker 10A has lifted negativepressure reusable respirator 13A away from his face in response todetermining that the distance between the face of worker 10A andnegative pressure reusable respirator 13A satisfies a second thresholddistance, that worker 10A has not completed a wearer seal check thatsatisfies a least one threshold, information about the physical state ofa negative pressure reusable respirator 13A, or usage information abouta negative pressure reusable respirator 13A.

In some examples, analytics service 68F determines whether a particularworker satisfies one or more safety rules that are associated with aworker. In some examples, the safety rules associated with a worker mayinclude rules indicating a level of experience or training the workershould have to perform certain tasks or work in certain workenvironments. In some examples, analytics service 68F determines whetherworker 10A satisfies one or more safety rules associated with worker 10Abased at least in part on worker data 74C. For example, worker data 74Cmay include data indicating an experience level of each worker ofworkers 10, trainings received by each worker of workers 10, or acombination therein. Analytics service 68F may determine whether worker10A satisfies one or more safety rules of models 74B by querying workerdata 74C and comparing the worker data associated with worker 10A to thesafety rules. For instance, safety rules 74B may indicate one or moretraining a worker 10 must receive prior to using a particular negativepressure reusable respirator 13 (e.g., a particular type of negativepressure reusable respirator 13). Analytics service 68F may determinewhether worker 10A satisfies such a safety rule by querying worker data74C to determine whether worker 10A has been trained to use negativepressure reusable respirator 13A.

In some examples, notification service 68E outputs a notification inresponse to determine that a safety rule is not satisfied (e.g., aworker 10 does not satisfy a safety rule, or an article of PPE orcomponent of an article of PPE does not satisfy a safety rule). Forexample, notification service 68E may output the notification to atleast one of clients 63 (e.g., one or more of computing devices 60, hubs14, safety stations 15, or a combination therein). In some examples, thenotification indicates whether contaminant capture device 23A satisfiesthe one or more rules. The notification may indicate which worker ofworkers 10 is associated with the article or component that is due forreplacement, a location of the worker, a location at which a replacementis located, etc. In some examples, the notification may indicate that aworker is not clean shaven or has lifted a respirator away from his orher face. As another example, the notification may indicate that worker10A is not trained to utilize the particular negative pressure reusablerespirator 13.

FIG. 8 is a conceptual diagram illustrating an example negative pressurereusable respirator, in accordance with aspects of this disclosure.Negative pressure reusable respirator 13A is configured to receive(e.g., be physically coupled to) one or more contamination capturedevices 23A, such as a particulate filter, a chemical cartridge, orboth. Negative pressure reusable respirator 13A is configured tophysically couple to computing device 300. Negative pressure reusablerespirator 13A includes a facepiece (e.g., a full facepiece, or a halffacepiece) 301 configured to cover at least a worker's nose and mouth.In some examples, computing device 300 is located with facepiece 301. Itshould be understood that the architecture and arrangement of negativepressure reusable respirator 13A and computing device 300 illustrated inFIG. 8 is shown for exemplary purposes only. In other examples, negativepressure reusable respirator 13A and computing device 300 may beconfigured in a variety of other ways having additional, fewer, oralternative components than those shown in FIG. 8.

In the example of FIG. 8, contamination capture device 23A includes amemory device and a communication device, such as RFID tag (e.g.,passive RFID tag) 350. RFID tag 350 stores information corresponding tocontaminant capture device 23A (e.g., information identifying a type ofthe contaminant capture device 23A) and outputs the informationcorresponding to contaminant capture device 23A in response to receivinga signal from another communication device (e.g., an RFID reader).

Computing device 300 may be configured to physically couple to negativepressure reusable respirator 13A. In some embodiments, computing device300 is operably disposed on an accessory 11, where accessory 11 isoperably disposed on negative pressure reusable respirator 23. In someexamples, accessory 11 or computing device 300 may be disposed betweenfacepiece 301 of negative pressure reusable respirator 13A and a face ofworker 10A. For example, accessory 11 or computing device 300 may bephysically coupled to an inner wall of the respirator cavity. Accessory11 or computing device 300 may be integral with negative pressurereusable respirator 13A or physically separable from negative pressurereusable respirator 13A. In some examples, accessory 11 or computingdevice 300 is physically separate from negative pressure reusablerespirator 13A and communicatively coupled to negative pressure reusablerespirator 13A. For example, computing device 300 may be a smartphonecarried by worker 10A or a data hub worn by worker 10A.

Computing device 300 includes one or more processors 302, one or morestorage devices 304, one or more communication units 306, one or moresensors 308, one or more output units 318, sensor data 320, models 322,and worker data 324. Processors 302, in one example, are configured toimplement functionality and/or process instructions for execution withincomputing device 300. For example, processors 302 may be capable ofprocessing instructions stored by storage device 304. Processors 302 mayinclude, for example, microprocessors, digital signal processors (DSPs),application specific integrated circuits (ASICs), field-programmablegate array (FPGAs), or equivalent discrete or integrated logiccircuitry.

Storage device 304 may include a computer-readable storage medium orcomputer-readable storage device. In some examples, storage device 304may include one or more of a short-term memory or a long-term memory.Storage device 304 may include, for example, random access memories(RAM), dynamic random access memories (DRAM), static random accessmemories (SRAM), magnetic hard discs, optical discs, flash memories, orforms of electrically programmable memories (EPROM) or electricallyerasable and programmable memories (EEPROM).

In some examples, storage device 304 may store an operating system orother application that controls the operation of components of computingdevice 300. For example, the operating system may facilitate thecommunication of data from electronic sensors 308 to communication unit306. In some examples, storage device 304 is used to store programinstructions for execution by processors 302. Storage device 304 mayalso be configured to store information within computing device 300during operation. In some examples, storage device 304 may also beconfigured to transmit information from to a second device, such as forexample, a remote wearer 24, a computing device 16, 18 that may belocated remote from storage device 304, and combinations thereof. Insome embodiments, the second device is integral or separate from storagedevice 304.

Storage device 304 is configured to store information related to atleast one of: a time; a time duration; a state of the negative pressurereusable respirator; usage information relating to the negative pressurereusable respirator; whether at least one contaminant capture devicecoupled to a negative pressure reusable respirator is due forreplacement; whether usage of the negative pressure reusable respiratorsatisfies one or more safety rules associated with the negative pressurereusable respirator; sensor data; or combinations thereof.

Computing device 300 may use one or more communication units 306 tocommunicate with external devices via one or more wired or wirelessconnections. Communication units 306 may include various mixers,filters, amplifiers and other components designed for signal modulation,as well as one or more antennas and/or other components designed fortransmitting and receiving data. Communication units 306 may send andreceive data to other computing devices using any one or more suitabledata communication techniques. In some embodiments, the other computingdevices, such as a second device, are integral or separate fromcomputing device 300. Examples of such communication techniques mayinclude TCP/IP, Ethernet, Wi-Fi, Bluetooth, 4G, LTE, to name only a fewexamples. In some instances, communication units 306 may operate inaccordance with the Bluetooth Low Energy (BLU) protocol. In someexamples, communication units 306 may include a short-rangecommunication unit, such as an RFID reader.

In general, computing device 300 includes a plurality of sensors 308,such as a first sensor and a second sensor, that generate sensor dataindicative of operational characteristics of negative pressure reusablerespirator 13A, contaminant capture devices 23A, and/or an environmentin which negative pressure reusable respirator 13A is used. Sensors 308may include an accelerometer, a magnetometer, an altimeter, anenvironmental sensor, among other examples. In some examples,environment sensors may include one or more sensors configured tomeasure temperature, humidity, particulate content, gas or vaporconcentration levels, or any variety of other characteristics ofenvironments in which negative pressure reusable respirator 13A areused. In some examples, one or more of sensors 308 may be disposedbetween facepiece 301 of negative pressure reusable respirator 13A and aface of worker 10A. For example, one of sensors 308 (e.g., an airpressure sensor) may be physically coupled to an inner wall of therespirator cavity.

In an example of FIG. 8, sensors 308 include one or more air pressuresensors 310 configured to measure air pressure within a cavity formed ordefined by a face of worker 10A and negative pressure reusablerespirator 13A. In other words, air pressure sensors 310 detect the airpressure of the air located in the sealable space between the face ofworker 10A and facepiece 301 as the worker inhales and exhales.

In an example of FIG. 8, sensors 308 also include one or more valveposition sensor 311 configured to generate data indicative of a positionof the at least one valve in the negative pressure reusable respirator13A. In some instances as shown in FIG. 8, sensors 308 include a firstsensor, such as one or more air pressure sensors 310, configured togenerate first sensor data indicative of a gas characteristic in asealed space formed by a face of the wearer and the negative pressurereusable respirator 13A and a second sensor, such as a valve positionsensor 311, configured to generate second sensor data indicative of aposition of the at least one valve.

Computing device 300 includes one or more output units 318 configured tooutput data that is indicative of operation of negative pressurereusable respirator 13A. In some examples, output unit 318 output datafrom the one or more sensors 308 of negative pressure reusablerespirator 13A. For example, output unit 318 may generate one or moremessages containing real-time or near real-time data from one or moresensors 308 of negative pressure reusable respirator 13A fortransmission to another device via communication unit 306. In someexamples, output unit 318 are configured to transmit the sensor data inreal-time or near-real time to another device (e.g., safety equipment62) via communication unit 306. However, in some instances,communication unit 306 may not be able to communicate with such devices,e.g., due to an environment in which negative pressure reusablerespirator 13A is located and/or network outages. In such instances,output unit 318 may cache usage data to storage device 304. That is,output unit 318 (or the sensors themselves) may send usage data tostorage device 304, e.g., as sensor data 320, which may allow the usagedata to be uploaded to another device upon a network connection becomingavailable.

In some examples, output unit 318 is configured to generate an audible,visual, tactile, or other output that is perceptible by a worker ofnegative pressure reusable respirator 13A. Examples of output are audio,visual, or tactile output. For example, output units 318 include onemore worker interface devices including, as examples, a variety oflights, displays, haptic feedback generators, speakers or the like.Output units 318 may interpret received alert data and generate anoutput (e.g., an audible, visual, or tactile output) to notify a workerusing negative pressure reusable respirator 13A of an alert condition(e.g., that the likelihood of a safety event is relatively high, thatthe environment is dangerous, that negative pressure reusable respirator13A is malfunctioning, that one or more components of negative pressurereusable respirator 13A need to be repaired or replaced, or the like).

According to aspects of this disclosure, processors 302 utilize sensordata (e.g., data from pressure sensors 310, valve position sensors 311,environmental sensors 312, and/or infrared sensors 314 of computingdevice 300, data from sensing stations 21 of FIG. 5, or other sensors)in a variety of ways. In some examples, processors 302 are configured toperform all or a portion of the functionality of PPEMS 6 described inFIGS. 1 and 2. While processors 302 are described as performing thefunctionality in FIG. 8, in some examples, other devices (e.g., PPEMS 6,hubs 14, other devices, or a combination therein) perform functionalitydescribed with reference to processors 302.

In the example of FIG. 8, computing device 300 includes sensor data 320,models 322, and worker data 324. Sensor data 320 includes data regardingoperation of negative pressure reusable respirator 13A, physiologicalconditions of worker 10A, characteristics of environment 8B, or acombination thereof. In other words, sensor data 320 may include datafrom PPE sensors, physiological sensors, and/or environmental sensors.Models 322 include historical data (e.g., historical sensor data) andmodels, such as models 74B described with reference to FIG. 7. Workerdata 324 may include worker profiles, such as worker data 74C describedwith reference to FIG. 7.

Processors 302 may determine comparative data by comparing first sensordata to second sensor data, where a first sensor, such as an airpressure sensor 310, is configured to generate first sensor dataindicative of a gas characteristic in a sealed space formed by a face ofthe wearer and the negative pressure reusable respirator, and a secondsensor, such as a valve position sensor 311, is configured to generatesecond sensor data indicative of a position of the at least one valve.In some instances, first sensor data and second sensor data are storedin sensor data 320. In some instances, processors 302 apply one or moremodels 322 to sensor data 320 to determine a gas characteristic in asealed space formed by a face of the wearer and the negative pressurereusable respirator and a position of the at least one valve in thenegative pressure reusable respirator. In some examples, models 322 maybe trained based on historical data (e.g., air pressure data,physiological sensor data). In some instances, such historical data mayrelate to an individual wearer, aggregated from a group of wearers, or acombination thereof.

In some embodiments, processors 302 may determine whether contaminationcapture devices 23A are due for replacement based at least in part onair pressure data generated by air pressure sensors 310 or environmentaldata generated by an environmental sensors 312 (additionally oralternatively, by sensing stations 21 of FIG. 5). In some instances,processors 302 apply one or more models 322 to sensor data 320 todetermine whether contamination capture devices 23A are due forreplacement. In some examples, models 322 may be trained based onhistorical data (e.g., air pressure data, physiological sensor data).For example, models 322 may be trained on historical air pressure dataassociated with worker 10A, historical physiological data, andhistorical worker feedback from worker 10A indicating worker 10A ishaving difficulty breathing, which may indicate that a particulatefilter of contamination capture device 23A is saturated and/or due forreplacement. In such examples, processors 302 apply models 322 topredict when contamination capture devices 23A are due for replacementbased on current (e.g., real-time, or near real-time) air pressure datafrom air pressure sensors 310.

In some examples, models 322 are trained on historical environmentaldata (e.g., indicative of gas or vapor concentration levels) generatedby environmental sensors 312 or sensing stations 21 of FIG. 5 andhistorical determinations of contaminant capture device lifespan.Processors 302 may apply models 322 to current environmental sensor datato determine a threshold exposure time and compare an actual exposuretime to the threshold exposure time to determine whether contaminantcapture device 23A is due for replacement. As another example,processors 302 may apply models 322 to current environmental sensor datato determine a cumulative consumption and compare the cumulativeconsumption to a threshold consumption to determine whether contaminantcapture device 23A is due for replacement.

In some examples, processors 302 determine whether the sealable spacebetween a face of worker 10A and respirator 13A is sealed. The sealablespace may not be sealed when there is a leak in the seal, whenrespirator 13A is not properly positioned on the face of worker 10A, orwhen worker 10A removes respirator 13A. Processors 302 may determinewhether the sealable space is sealed based at least in part on the airpressure data. For example, processors 302 may compare the pressure to abaseline pressure (e.g., a pressure when respirator 13A is known toprovide a seal) and determine that the seal is broken in response todetermining that the pressure does not satisfy the baseline pressure. Insuch examples, output units 318 may output an alert indicating apossible leak in the seal.

In some examples, processors 302 determine whether negative pressurereusable respirator 13A and/or contaminant capture device 23A satisfiesone or more safety rules associated with a particular work environment(e.g., environment 8B of FIG. 5). In some instances, safety rules arepre-programmed rules related to some attribute of the negative pressurereusable respirator, such as for example usage, performance, wearer fit,and the like. In some instances, safety rules are stored in storagedevice 304 integral to the negative pressure reusable respirator 13A. Insome instances, safety rules generated by processors 302 compare usageof wearer's negative pressure reusable respirator 13A to data externalto the computing device 300.

In some examples, the safety rules may indicate that respirator 13Ashould be worn. In some examples, infrared sensor 314 outputs dataindicative of whether respirator 13A is worn. In some embodiments,infrared sensor 314 outputs data indicative of whether at least onevalve had any position changes. For example, the infrared sensor datamay include data indicating a distance between respirator 13A or atleast one valve 9 and the nearest object. In some instances, processors302 determine whether respirator 13A is worn by comparing the distanceto a threshold distance. For instance, the threshold distance may be adistance between facepiece 301 and the face of worker 10A when worker10A is known to be wearing respirator 13A. In other examples, thethreshold distance may be a distance between the at least one valve 9and a portion of respirator 13A when worker is known to be respiratingthrough the at least one valve 9. As another example, the infraredsensor data may include temperature data. Processors 302 may determinewhether respirator 13A is worn by comparing the temperature data to athreshold temperature that is indicative of a human body (e.g.,approximately 98.6 degrees Fahrenheit or approximately 37 degreesCelsius).

In some instances, the safety rules indicate that a contaminant capturedevice 23A should be physically coupled to respirator 13A. In suchinstances, processors 302 determine whether contaminant capture device23A is present (e.g., attached to respirator 13A) by causingcommunication units 306 to emit an RFID signal and determining whethercommunication units 306 receive a signal that includes identificationinformation for a contaminant capture device 23. In one example,processors 302 determine that a contaminant capture device 23 is notpresent when identification information is not received and determinethat a contaminant capture device 23 is present identificationinformation is received.

Processors 302 may determine whether contaminant capture devices 23Asatisfies the safety rules based at least in part on data received fromthe contaminant capture device 23A. For instance, contaminant capturedevice 23A may include RFID tag 350 that stores identificationinformation corresponding to the contaminant capture device 23A (e.g.,information identifying a type of the contaminant capture device 23A).Processors 302 may receive the identification information forcontaminant capture device 23A. For instance, models 322 may includedata indicative of one or more safety rules, such as indicating the typeof contaminant capture device 23A associated with various hazards orenvironments.

Processors 302 determine, in some examples, whether contaminant capturedevice 23A satisfies a safety rule by determining whether contaminantcapture device 23A is authentic. In some examples, processors 302determine whether contaminant capture device 23A is authentic based onthe identification information. For example, processors 302 mayauthenticate the contaminant capture device by comparing the receivedidentification information to known authentication information. In someinstances, equipment data 326 includes authentication information forauthentic or verified contaminant cartridge devices. In such instances,processors 302 may query equipment data 326 to determine whethercontaminant capture device 23A is authentic. In other example,processors 302 query a remote computing device (e.g., PPEMS 6) viacommunication units 306 to determine whether contaminant capture device23A is authentic. For example, processors 302 may output a notificationto PPEMS 6 that includes the identification information of contaminantcapture device 23A and a request for PPEMS 6 to authenticate theidentification information. Responsive to determining that contaminantcapture device 23A is not present or is not authentic, computing device300 may output a notification (e.g., to PPEMS 6) indicating thatcontaminant capture device 23A is not present or is not authentic. Insome examples, output units 318 output an alert (e.g., audible, visual,haptic) indicating that contaminant capture device 23A is not present oris not authentic in response to determining that that contaminantcapture device 23A is not present or is not authentic.

In some examples, processors 302 determine, based on the identificationinformation and models 322, whether contaminant capture device 23Asatisfies the safety rules by determining whether the type of thecontaminant capture device 23A corresponds to (e.g., is a same orsimilar to) the type of the contaminant capture device associated withthe environment or hazards within the environment. In other words,processors 302 may determine whether contaminant capture device 23A isthe right type of particulate filter or chemical cartridge to protectworker 10A in the work environment.

Processors 302 may determine whether usage of one or more negativepressure reusable respirator 13A satisfies one or more safety rulesassociated with worker 10A. In some examples, the safety rules areassociated with conditions indicating whether a worker is clean shavenor lifts a respirator from his or her face. In some examples, processors302 determines whether usage of negative pressure reusable respirator13A satisfies a safety rule by determining whether worker 10A is cleanshaven or lifts negative pressure reusable respirator 13A from his orher face. In one example, processors 302 determine whether worker 10A isclean shaven by determining a distance between negative pressurereusable respirator 13A and the face of worker 10A and comparing thedistance to a threshold distance. For instance, processors 302 mayreceive data indicating the distance between negative pressure reusablerespirator 13A and the face of worker 10A from infrared sensor 314, suchthat processors 302 determine that worker 10A is not clean shaven inresponse to determining that the distance satisfies (e.g., is greaterthan) a first threshold distance associated with worker 10A. In anotherexample, processors 302 determine that worker 10A has lifted respirator13A from his or her face in response to determining that the distancesatisfies (e.g., is greater than) a second threshold distance.

In some examples, processors 302 determine whether worker 10A satisfiesone or more safety rules that are associated with worker 10A. Forexample, processors 302 may determine whether worker 10A has theexperience or training to work in a particular environment (e.g.,environment 8B of FIG. 5), perform a particular task, operate aparticular type of equipment, utilize a particular type of respirator,etc. For instance, worker data 324 includes a worker profile indicatingan experience level of worker 10A, trainings received by worker 10A,demographic data (e.g., age) for worker 10A, medical data for worker10A, whether worker 10A has been fitted for a particular type ofrespirator 13A, among other data. Worker data 324 includes workerprofiles for worker 10A and additional workers 10. In one example,processors 302 apply one or more models 322 to worker data 324 (e.g., aworker profile) to determine whether worker 10A satisfies one or moresafety rules. For example, processors 302 may determine whether worker10A has been trained in hazards associated with the work environment inwhich worker 10A is located. As another example, processors 302 maydetermine whether worker 10A has been trained in the type of respirator13A and/or contaminant capture device 23A associated with hazards inenvironment 8B. In some instances various sensors and thresholds may beused together to determine various performance, usage or physical statesof respirator 13A.

Output units 318 output one or more alerts in response to determiningthat negative pressure reusable respirator 13A and/or contaminantcapture device 23A satisfies one or more safety rules associated with aparticular work environment. In one example, output units 318 includeone or more light sources that emit light (e.g., of one or more color)indicative of a status of the negative pressure reusable respirator 13A.For instance, output unit 318 may output light of a first color (e.g.,green) to indicate a normal status, light of a second color (e.g.,yellow) to indicate contaminant capture device 23A is approaching timefor replacement, and a light of a third color to indicate contaminantcapture device 23A is due for immediate replacement. In another example,output units 318 output an alert in response to determining that usageof one or more negative pressure reusable respirator 13A satisfies oneor more safety rules or in response to determining that worker 10Asatisfies one or more safety rules. For example, output units 318 mayoutput light of a first color in response to determining that worker 10Adoes not satisfy a safety rule (e.g., is not trained on a particulartype of negative pressure reusable respirator 13A) or output light of asecond color in response to determining that contaminant capture device23A does not satisfy a safety rule (e.g., does not protect againsthazards known to be present in the work environment).

In some examples, output units 318 output notifications to one or moreother computing devices (e.g., hub 14A of FIG. 5, PPEMS 6 of FIG. 5, orboth) via communication units 306. For example, the notification mayinclude data indicating the identity of worker 10A, an environment 8B inwhich worker 10A is located, whether one or more safety rules aresatisfied, among others. In some examples, the notification may indicatethat a contaminant capture device 23A is due for replacement, thatworker 10A is not clean shaven, that worker 10A has not completed awearer seal check that satisfies a least one threshold, that worker 10Ahas lifted negative pressure reusable respirator 13A from his or herface, information about the physical state of a negative pressurereusable respirator, or usage information about a negative pressurereusable respirator.

FIG. 13 is a flowchart illustrating example operations of an examplecomputing system, in accordance with various techniques of thisdisclosure. FIG. 13 is described below in the context of negativepressure reusable respirator 13A of FIG. 5, PPEMS 6 of FIGS. 4 and 2,and/or computing device 300 of FIG. 8. While described in the context ofnegative pressure reusable respirator 13A, PPEMS 6, and/or computingdevice 300, other computing devices (e.g., a hub of hubs 14 of FIG. 5)may perform all or a subset of the functionality described.

In some examples, at least one computing device receives sensor dataindicative of a characteristic of air within a work environment (402).For example, negative pressure reusable respirator 13A may include acomputing device 300 or may be configured to physically couple tocomputing device 300. In other words, computing device 300 may beintegrally formed within negative pressure reusable respirator (e.g.,non-removable) or may be attachable/detachable, such as for example asbeing operably disposed on at least one accessory 11, where accessory 11is operably disposed on and internal or external surface of negativepressure reusable respirator 13A. In one instance, computing device 300receives sensor data from one or more sensors configured to generatesensor data indicative of a characteristic of air within a workenvironment. Additionally or alternatively, PPEMS 6 may receive thesensor data. In one example, the sensor data includes data generated bya first sensor, such as an air pressure sensor 310 used to indicate airpressure within a sealable or sealed space formed (e.g., defined) by aface of worker 10A and negative pressure reusable respirator 13A. Inanother example, the sensor data includes data generated by a secondsensor, such as a valve position sensor 311 used to indicate position ofat least valve in negative pressure reusable respirator 13A. In oneexample, the sensor data includes data generated by a first sensor, suchas an air pressure sensor 310 used to indicate air pressure within asealable or sealed space formed (e.g., defined) by a face of worker 10Aand negative pressure reusable respirator 13A and data generated by asecond sensor, such as a valve position sensor 311 used to indicateposition of at least valve in negative pressure reusable respirator 13A.As another example, the sensor data may include data generated by anenvironmental sensor (e.g., environmental sensor 312 or sensing stations21), such as environmental data indicative of a gas or vaporconcentration level within a work environment (e.g., environment 8B ofFIG. 5).

The at least one computing device determines, based at least in part onthe sensor data, various usage or physical state information about thenegative pressure reusable respirator. For example, the at least onecomputing device determines, based at least in part on the sensor data,whether at least one contaminant capture device coupled to a negativepressure reusable respirator is due for replacement (404). For example,the at least one computing device may determines whether at least onecontaminant capture device 23A is due for replacement based at least inpart on air pressure data, environmental data, or both. In someexamples, computing device 300 and/or PPEMS 6 determines whether atleast one contaminant capture device 23A is due for replacement based atleast in part on data from air pressure data. For example, PPEMS 6and/or computing device 300 may determine whether the air pressurewithin the sealable space formed by the worker's face and negativepressure reusable respirator 13A decreases below a threshold airpressure when the worker inhales.

In some examples, PPEMS 6 and/or computing device 300 determine whetherthe at least one contaminant capture device 23A is due for replacementbased at least in part on the environmental data. According to someexamples, PPEMS 6 and/or computing device 300 determines a thresholdexposure time for the contaminant capture device 23A based on theenvironmental data (e.g., gas or vapor concentration level) and comparesthe actual exposure time for contaminant capture device 23A to thethreshold exposure time. As another example, the computing device 300and/or PPEMS 6 may determine a cumulative consumption of the contaminantcapture device 23A and compare the cumulative consumption of thecontaminant capture device 23A to a threshold consumption to determinewhether contaminant capture device 23A is due for replacement.

At least one computing device performs one or more actions in responseto determining the at least one contaminant capture device is due forreplacement (406). In some examples, PPEMS 6 outputs a notification toanother computing device (e.g., computing devices 16, 18 of FIG. 5)indicating contaminant capture device 23A is due for replacement. Inanother example, output unit 318 of computing device 300 outputs analert indicating that contaminant capture device 23A is due forreplacement.

According to some examples, at least one computing device determines,based on the data indicative of a position of the negative pressurereusable respirator relative to the face of the worker, whether usage ofthe negative pressure reusable respirator satisfies one or more safetyrules associated with the negative pressure reusable respirator. In someinstances, computing device 300 receives sensor data from an infraredsensor 314, the sensor data indicating a distance between negativepressure reusable respirator 13A and a face of worker 10A. In oneinstance, computing device 300 and/or PPEMS 6 determine, based on thedistance, whether worker 10A is clean shaven and/or whether negativepressure reusable respirator 13A has been lifted from the face of worker10A.

In some examples, PPEMS 6 and/or computing device 300 determine whethercontaminant capture device 23A satisfies one or more safety rulesassociated with work environment 8B. In one example, contaminant capturedevice 23A include an RFID tag 350 and a communication unit 306 ofcomputing device 300 includes an RFID reader. In such examples, one ofcommunication units 306 receives identification information forcontaminant capture device 23A from RFID tag 352 and determines whethercontaminant capture device 23A satisfies one or more safety rulesassociated with the environment based on the identification information.For example, computing device 300 may determine whether contaminantcapture device 23A fits negative pressure reusable respirator 13A orwhether contaminant capture device 23A is configured to protect worker10A from hazards associated with environment 8B.

FIG. 14 is a flowchart illustrating example operations of an examplecomputing system, in accordance with various techniques of thisdisclosure. FIG. 15 is described below in the context of negativepressure reusable respirator 13A of FIG. 5, PPEMS 6 of FIGS. 4 and 2,and/or computing device 300 of FIG. 8. While described in the context ofnegative pressure reusable respirator 13A, PPEMS 6, and/or computingdevice 300, other computing devices (e.g., a hub of hubs 14 of FIG. 5)may perform all or a subset of the functionality described.

In some examples, at least one computing device receives first sensordata indicative of a gas characteristic in a sealed space formed by aface of the wearer and the negative pressure reusable respirator (502).In some examples, at least one computing device receives second sensordata configured to generate second sensor data indicative of a positionof the at least one valve (504). For example, negative pressure reusablerespirator 13A may include a computing device 300 or may be configuredto physically couple to computing device 300. In other words, computingdevice 300 may be integrally formed within negative pressure reusablerespirator (e.g., non-removable) or may be attachable/detachable, suchas for example as being operably disposed on at least one accessory 11,where accessory 11 is operably disposed on and internal or externalsurface of negative pressure reusable respirator 13A. In one instance,computing device 300 receives sensor data from one or more sensorsconfigured to generate sensor data indicative of a characteristic of airwithin a work environment. Additionally or alternatively, PPEMS 6 mayreceive the sensor data. In one example, the sensor data includes datagenerated by a first sensor, such as an air pressure sensor 310 used toindicate air pressure within a sealable or sealed space formed (e.g.,defined) by a face of worker 10A and negative pressure reusablerespirator 13A. In another example, the sensor data includes datagenerated by a second sensor, such as a valve position sensor 311 usedto indicate position of at least valve in negative pressure reusablerespirator 13A. In one example, the sensor data includes data generatedby a first sensor, such as an air pressure sensor 310 used to indicateair pressure within a sealable or sealed space formed (e.g., defined) bya face of worker 10A and negative pressure reusable respirator 13A anddata generated by a second sensor, such as a valve position sensor 311used to indicate position of at least valve in negative pressurereusable respirator 13A. As another example, the sensor data may includedata generated by an environmental sensor (e.g., environmental sensor312 or sensing stations 21), such as environmental data indicative of agas or vapor concentration level within a work environment (e.g.,environment 8B of FIG. 5).

The at least one computing device determines comparative data bycomparing first and second sensor data to determine usage information orphysical state information related to negative pressure reusablerespirator 13A (506). In some embodiments, both usage information andphysical state information is determined. For example, PPEMS 6 and/orcomputing device 300 may determine, based in first sensor data, whetherthe air pressure within the sealable space formed by the worker's faceand negative pressure reusable respirator 13A decreases below athreshold air pressure when the worker inhales.

At least one computing device performs one or more actions in responseto comparative data (508). In some examples, PPEMS 6 outputs anotification to another computing device (e.g., computing devices 16, 18of FIG. 5) indicating usage or physical state information about thenegative pressure reusable respirator. In another example, output unit318 of computing device 300 outputs an alert to wearer indicating usageor physical state information about the negative pressure reusablerespirator. In some embodiments, output unit 318 of computing device 300outputs an alert to wearer indicating usage and physical stateinformation about the negative pressure reusable respirator.

FIG. 15 is an interior perspective view of a portion of a negativepressure reusable respirator according to some embodiments of thepresent disclosure in which a computing device is operably coupled to apressure sensor and at least one other sensor. FIG. 15 illustratesreusable respirator 13. Reusable respirator 13 may include similar orthe same components, structure, and functionalities as described inFIGS. 4A-4D. In some examples, components, structure, andfunctionalities as described in FIGS. 4A-4D may be adapted or otherwisemodified based on the examples of FIG. 15 or other examples of thisdisclosure.

FIG. 15 illustrates reusable respirator 13 and computing device 300 fordetermining state and usage information. In some examples, one or moreacoustic sensors 1500 are included to determine information related torespirator fit and/or seal. Acoustic sensor 1500 may receive and convertsound waves into one or more electrical signals. The electrical signalsmay represent intensity, frequency, duration, variation or any otherproperties of the sound waves. Example acoustic sensors may include aGrove Acoustic sensor, http://wiki.seeedstudio.com/Grove-Sound_Sensor,accessed Nov. 26, 2019 and SunFounder Acoustic sensor Module,https://www.sunfounder.com/sound-sensor-module.html, accessed Nov. 26,2019, the entire contents of each of which are hereby incorporated byreference herein in their entireties. Although the foregoing acousticsensors are provided as examples, any suitable acoustic sensor that maybe integrated (physically and/or operably) with computing device 300 andthat may convert sound waves into one or more electrical signals may beused in accordance with techniques of this disclosure.

Rather than providing a respirator with ultraacoustic sensors locatedexternal to the sealed space of a respirator that are configured tomerely detect either sounds generated by nasal breathing or soundsgenerated by an ultrasound emitter located internal to the sealed spaceof the respirator, example systems and techniques of FIG. 15 may use acombination of sensor data indicative of a gas characteristic in thesealed space of a respirator with sensor data indicative of sound todetermine state and/or usage information of a respirator. Such stateand/or usage information may not be determined by either sensor alone,or in other cases, such state and/or usage information may besignificantly improved by the combination of sensor data.

In contrast to other conventional techniques, computing device 300 ofFIG. 15 may automatically determine that a respirator is being worn andfurther determine, based at least in part by using data from acousticsensor 1500, one or more performance characteristics of a respiratorseal check by the wearer. Examples of performance characteristics mayinclude the initiation of a seal check, the completion of a seal check,a time duration of a seal check, information associated with the qualityof a seal during a seal check, such as leakage through a seal or a passor fail indication of a seal check, and the like. In some examples, theperformance of the respirator seal check indicates whether therespirator seal check has passed or failed. In some examples, theperformance of the respirator seal check indicates a degree of leakageof air external to the sealed space into the sealed space. In contrastto other conventional techniques, computing device 300 of FIG. 15 mayautomatically determine the occurrence of a respirator seal check by awearer and further determine, at least in part by using data from anacoustic sensor, information related to the seal of a respirator. Suchinformation related to the seal of the respirator may include, but isnot limited to: leakage into, out of, through or around a respiratorseal; missing respirator components; leakage around an object used toseal a respirator flow path, such as a wearers hands or a valve; leakageassociated with an action; leakage associated with a time period;leakage associated with a pressure differential; and/or a level ofleakage.

In some instances, the systems and techniques of FIG. 15 may moreaccurately determine safety information in a shorter amount of time,creating an improved experience for an end user. Systems and techniquesof FIG. 15 may provide a respirator system that can automaticallydetermine both that a respirator is being worn and the performance of arespirator seal check by a wearer, based at least in part on sound.Acoustic sensors are decreasing in size and may be placed within arespirator. Systems and techniques of FIG. 15 may not require trainedaction by a user to initiate the sensor-based assessment of a sealcheck, in contrast to conventional methods which may require aspecifically initiated, or learned, user action to initiate thesensor-based assessment of a seal check, such as initiating a computerapplication, or generating a specific signal spike. A system thatrequires no new trained user action, such as in FIG. 15, may save timeand/or implementation costs for users.

In some instances, the systems and techniques of FIG. 15 may provide arespirator system that can automatically determine the occurrence of arespirator seal check conducted by a wearer and further determineinformation related to the quality of the seal of the respirator, basedat least in part on sound. In contrast to conventional methods, thesystems and techniques of FIG. 15 may automatically determine theoccurrence of a respirator seal check with no new trained user actionand further determine the quality of the seal based at least in part ondata from a sensor indicative of sound. In some instances, it may bemost beneficial to only use the data from acoustic sensor 1500 after orin response to the occurrence of a seal check that has already beendetermined. In some noisy environments, sound data may not be suitablyreliable to determine that a respirator seal check has started but maybe suitably reliable to determine information related to the seal oncethe occurrence of a seal check is already known. Systems and techniquesof FIG. 15 may configure an acoustic sensor to operate in a low powerstate until a seal check occurs, which may provide power savings thatcan allow for smaller and/or lighter weight power sources, which mayprovide for a more comfortable respirator.

FIG. 15 illustrates a negative pressure reusable respirator 13configured to be worn by a wearer and to cover at least a mouth and anose of the wearer 10 to form a sealed space formed by a face of thewearer 10 and the negative pressure reusable respirator 13. Negativepressure reusable respirator 10 may also include at least one accessory11, such as illustrated in FIG. 5. In some embodiments, accessory 11 isoperably disposed within the sealed space. In some embodiments,accessory 11 is operably disposed on an external surface of the negativepressure reusable respirator 13. In some embodiments, accessory 11includes a computing device 300. In some embodiments, accessory 11includes at least one output device, such as for example, a speaker, ahaptic device, a light, a graphic display device, and the like. Afterthe wearer dons negative pressure reusable respirator 13, he/she canapply pressure to at least one contaminant capture device, in someembodiments two contaminant capture devices, inhale, and hold his/herbreath or continue to inhale to maintain a negative pressure.Alternatively, after the wearer dons negative pressure reusablerespirator 13, he/she can apply pressure to at least one exhalationvalve or exhalation outlet path, exhale, and hold his/her breath orcontinue to exhale to maintain a positive pressure. In some embodiments,after a course of events, such as those presently disclosed below, theoutput device of accessory 11 provides at least one alert to wearer 10.

In some embodiments, negative pressure reusable respirator 13 mayinclude at least one sensor 1500 (e.g., acoustic sensor 1500) configuredto generate sensor data indicative of sound. In some embodiments, the atleast one sensor 1500 is physically coupled to accessory 11. In someembodiments, the at least one sensor 1500 is physically coupled tonegative pressure reusable respirator 13.

Sound waves may be generated by the use of a respirator, due to thecreation of vibrational waves through the surrounding gas or therespirator itself, and these sound waves may be detected by a sensorconfigured to detect sound, such as acoustic sensor 1500. Sound wavesmay occur at different frequencies and different frequencies maysuperimpose to form additional signals, all of which may be detected byan appropriate sensor. For example, the movement of air through, or inproximity to, a respirator may result in measurable sounds wherein theparameters of the sound, such as frequency and/or intensity, are relatedto the specific movement of the air. For example, measurable soundparameters may be correlated to information related to breathing throughthe respirator, leaks in a respirator seal, obstruction of a respiratorcomponent, movement of respirator components such as valves, physicalcontact of the respirator, sounds generated by a wearer, orenvironmental sources of sound. In some examples, an appropriateacoustic sensor may be a microphone, an ultraacoustic sensor, or similarsuch sensors which are configured to detect vibrational waves through amedium.

In some embodiments, computing device 300 may determine physical stateinformation related to the negative pressure reusable respirator 300based at least in part on data from acoustic sensor 1500 that isconfigured to generate sensor data indicative of sound. In someexamples, the physical state may be selected from at least one of:presence of physical components of the negative pressure reusablerespirator; performance metrics of physical components of the negativepressure reusable respirator; pressure drop of the negative pressurereusable respirator; pressure drop of the negative pressure reusablerespirator at different air flow rates through the respirator; ambienttemperature; temperature within the negative pressure reusablerespirator; composition of ambient gases in the workplace; compositionof gases within the negative pressure reusable respirator; and anycombinations thereof. In some embodiments, computing device 300 may befurther configured to determine a change in at least one physical stateof negative pressure reusable respirator 13.

In some embodiments, computing device 300 may determine that negativepressure reusable respirator 13 is being worn by a wearer. Computingdevice 300 may additionally determine, based at least in part on thedata indicative of a sound, the performance of a respirator seal checkby a wearer. In some embodiments, computing device 300 may determineusage information related to the negative pressure reusable respirator300 based at least in part on data from acoustic sensor 1500 configuredto generate sensor data indicative of sound. In some embodiments, usageinformation is selected from at least one of: donning of the negativepressure reusable respirator 13; doffing of the negative pressurereusable respirator 13; occlusion of an inhalation path of the negativepressure reusable respirator 13; occlusion of an exhalation path of thenegative pressure reusable respirator 13; occurrence of a wearer sealcheck; information related to a performance procedure of a wearer sealcheck; information related to quality of a seal formed by the face ofthewearer and the negative pressure reusable respirator 13; change in theseal formed by the face of the wearer and the negative pressure reusablerespirator 13; and any combination thereof.

In some embodiments a system, such as illustrated in FIG. 15, mayinclude a respirator 13, a first sensor 1500 configured to generate dataindicative of sound, a second sensor 3 indicative of a gascharacteristic in a sealed space formed by a face of a wearer andrespirator 13, and a computing device 300. In the example of FIG. 15,data from different sensors may be used to determine different statesand/or different usage information, and/or data from multiple sensorsmay be combined and/or compared to improve the determination of statesand/or usage information. As an example, data from the second sensor 3may be used to determine the stage of a respiratory cycle through arespirator, such as inhalation or exhalation, or other stage of use.Computing device 300 may then assign baseline values of data from thefirst sensor 1500 based on the stage of a respiratory cycle. This mayenable computing device 300 to assign, for example, baseline soundvalues adapted to the current environment, which may differ based ondiffering levels of background environmental sound over time. Past,present or future data may then be compared by computing device 300 (orother computing devices) to assigned baseline values. The process ofdetermining baseline values may also be used in reverse—the first sensor1500 may establish a stage of a respirator cycle, or other stage of use,and the computing device 300 may assign values of the second sensor asbaseline values during the established stage. In another embodiment,data from multiple sensors may be compared by the computing device 300.For example, data from an air pressure sensor 3 may be compared to datafrom a acoustic sensor 1500 as part of a determination of a physicalstate and/or usage of a respirator 13. Data may also be compared fromdifferent time periods of the same or different sensors, or differentsignal regimes, such as different frequencies, between the same ordifferent sensors. For example, sensor data may be filtered by aprocessor (e.g., in computing device 300 and/or in a sensor itself) toprovide signal information at multiple frequency bands for comparison.Comparisons may also be made between multiple sensors. For example, datamay be compared between a first acoustic sensor 1500, a second airpressure sensor 3, and a third valve position sensor (not shown) as partof a process for determining usage and/or state information.

FIG. 15 illustrates an example of a system comprising a respirator 13,an acoustic sensor 1500 configured to generate data indicative of sound,and a computing device 300, wherein the computing device is configuredto determine that a respirator is being worn, and then determineperformance information related to a respirator seal check based atleast in part on the acoustic sensor 1500. In some examples, computingdevice 300 determines that respirator 13 is being worn based at least inpart on data from a second sensor 3 that is different than the acousticsensor. The second sensor 3 may generate data indicative of air pressure(or a gas characteristic in a sealed space formed by a face of a wearerand a negative pressure reusable respirator). In some examples, the dataindicative of sound comprises data from a first time (or time period)and data from a second time (or time period) that is different from thefirst time. In some examples, the data indicative of sound comprisesdata from a first frequency (or range of frequencies) and a secondfrequency (or range of frequencies). In some examples, the first andsecond frequencies are different. In some examples, the first and secondranges may overlap or may not overlap. In some examples, the dataindicative of sound from a first time and/or first frequency is comparedto data from a second time and/or second frequency. For example, datafrom a first time may be sound data assigned as a baseline value, anddata from a second time may be sound data associated with a respiratorseal check and these values may be compared as part of a determinationof the quality of a respirator seal. In some examples, the data from thefirst time and/or the second time may include data from multiplefrequencies, wherein the ratio of sound levels at different frequenciesmay differ depending on the level of leakage associated with arespirator during a respirator seal check. In some examples, computingdevice 300 provides the comparative data. For example, in someembodiments, computing device 300 may receive, and assign to memory,sensor data from one or more sensors during a first time period and mayreceive second data from one or more sensors during a second timeperiod, and then provide a comparison of the sensor data from the firsttime period to the sensor data from a second time period. A comparisonmay include any number of computational operations, such as a ratio ofvalue, and multiplication of values, an addition of values, asubtraction of values, an application of one set of values that dependson the values of another set of values, or any other useful computationcombination of values. In some examples, computing device 300 providescomparative data between the sound data and data from at least one othersensor. In some examples, a performance information includes anoccurrence of a respirator seal check, a duration of time related to arespirator seal check, and/or information related to the quality of arespirator seal. In some examples, computing device 300 may beconfigured to generate alerts and/or notifications and/or send messagesbased on any of the foregoing examples. In some examples, acousticsensor 1500 and/or the computing device 300 may be physically oroperably coupled to the respirator 13. In some examples, acoustic sensor1500 and/or the computing device 300 may be physically or operablycoupled to or included within an accessory of computing device 300and/or respirator 13.

In some examples, a computing device may determine at least one ofpressure data or acoustic data satisfies a respective thresholdassociated with the at least one of pressure data or acoustic data. Insome examples, a computing device may determine at least one of afrequency or a frequency range indicated by the acoustic data. Thecomputing device may determine, based at least in part on the at leastone of the frequency or the frequency range, the performance of therespirator seal check. In some examples, a computing device maydetermine whether the at least one of the frequency or frequency rangeindicated by the acoustic data satisfies a threshold; and determine theperformance of the respirator seal check based at least in part onwhether the at least one of the frequency or frequency range indicatedby the acoustic data satisfies a threshold. In some examples, acomputing device may determine at least one of an amplitude or anamplitude range indicated by the acoustic data; and determine, based atleast in part on the at least one of the amplitude or the amplituderange, the performance of the respirator seal check. In some examples, acomputing device may determine whether the at least one of the amplitudeor amplitude range indicated by the acoustic data satisfies a threshold;and determine the performance of the respirator seal check based atleast in part on whether the at least one of the amplitude or amplituderange indicated by the acoustic data satisfies a threshold. In someexamples, at least one of the acoustic sensor or at least one othersensor is physically integrated at an interior surface of the negativepressure reusable respirator that covers at least the mouth and the noseof the wearer to form the sealed space. In some examples, at least oneof the acoustic sensor or at least one other sensor is physicallyintegrated in an accessory that includes the computing device configuredfor operable coupling to the acoustic sensor and the at least one othersensor, where in the accessory is configured to be removably attached tothe negative pressure reusable respirator. In some examples, to performthe at least one operation based at least in part on the performance ofthe respirator seal check, the at least one computing device isconfigured to generate an output comprising at least one of a visual,audible, or haptic output at an output interface. In some examples, toperform the at least one operation based at least in part on theperformance of the respirator seal check, the at least one computingdevice is configured to send a message to at least one other computingdevice. In some examples, the at least one computing device isconfigured to receive a message from at least one other computingdevice.

In some examples, FIG. 15 illustrates a system comprising a respirator13, a sensor 1500 configured to generate data indicative of sound, and acomputing device 300, wherein the computing device 300 is configured todetermine the occurrence of a respirator seal check, and determineinformation related to the seal of the respirator 13 based at least inpart on the acoustic sensor. Further examples of this disclosureillustrate and describe example sound data that may be used as part of adetermination of information related to the quality of the seal of arespirator 13. In some examples, computing device 300 may determine theoccurrence of a respirator seal check based at least in part on datafrom a second sensor 3 that is different than the acoustic sensor 1500,wherein the second sensor is indicative of air pressure (or a gascharacteristic in a sealed space formed by a face of a wearer and anegative pressure reusable respirator). In some examples, the dataindicative of sound comprises data from a first time (or time period)and data from a second time (or time period). The first and second timesor time periods may be different. In some examples, the data indicativeof sound comprises data from a first frequency (or range of frequencies)and a second frequency (or range of frequencies). In some examples, thefirst and second frequencies or ranges of frequencies may be differentand/or may overlap or may not overlap. In some examples, the data from afirst time and/or first frequency is compared by computing device 300 todata from a second time and/or second frequency. In some examples,computing device 300 provides the comparative data. In some examples,computing device 300 may provide comparative data between the sound dataand data from another sensor, for example, comparative data between anacoustic sensor and a pressure sensor, as a combination of operationsdescribed in FIGS. 16 and 20. In some examples, the information relatedto the respirator seal comprises data from a first sensor 1500indicative of a sound and a second sensor 3 indicative of a gascharacteristic in a sealed space formed by a face of a wearer and anegative pressure reusable respirator. In some examples, performanceinformation may include the occurrence of a respirator seal check, theduration of time related to a respirator seal check, and/or informationrelated to the quality of a respirator seal. In some examples, computingdevice 300 may be configured to generate alerts and/or notificationsand/or send messages based on any of the foregoing examples. In someexamples, acoustic sensor 1500 and/or the computing device 300 may bephysically or operably coupled to the respirator 13. In some examples,acoustic sensor 1500 and/or the computing device 300 may be physicallyor operably coupled to or included within an accessory of computingdevice 300 and/or respirator 13.

In some examples, FIG. 15 illustrates a system comprising a respirator13, a first sensor 1500 configured to generate data indicative of sound,a second sensor 3 indicative of a gas characteristic in a sealed spaceformed by a face of a wearer and a negative pressure reusable respiratorand a computing device 300, wherein the computing device 300 isconfigured to provide comparative data by comparing the first sensordata to the second sensor data.

In some examples of FIG. 15, a respirator seal assessment apparatus 11is disclosed. The apparatus 11 may include a first sensor 1500configured to generate data indicative of sound, a second sensor 3configured to generate data indicative of a gas characteristic in asealed space formed by a face of a wearer and a negative pressurereusable respirator 13, and, a computing device 300 operativelyconnected to the first sensor and to the second sensor. The apparatus 11may be configured to be operatively coupled to a respirator 13. Thecomputing device 300 may determine that a respirator 13 is being wornbased at least in part on data from first sensor 1500, for example bydetecting acoustic changes due to breathing. The computing device 300may determine that a respirator 13 is being worn based at least in parton data from the second sensor 3, for example by detecting pressurechanges, air flow changes, temperature changes, composition changes, orthe like due to breathing. The computing device 300 may initiatenotifications to the wearer, to another computing device, or to anotherperson based on or indicating that the respirator is being worn and asatisfactory wearer seal check has not been conducted. Notifications tothe wearer may, as examples, take the form of visual, audible, or hapticfeedback such as lights, sounds, or vibrations. The computing device 300may then determine that a wearer seal check has begun based at least inpart of data from the second sensor satisfying a threshold. In someexamples, satisfying a threshold may include the data being greater thanequal to and/or less than a threshold value. For example, the computingdevice 300 may determine that a wearer seal check has begun and anegative pressure is detected (in some examples, that satisfies athreshold value) due to the wearer inhaling while covering or closingthe inhalation path, or when a positive pressure is detected (in someexamples, less than or equal to a threshold value) due to the wearerexhaling while covering or closing the exhalation path. The computingdevice 300 may generate notifications based on detecting a start of awearer seal check. The computing device 300 may then start a counting(or timer) operation. For example, the counting operation may comprisedetermining that a predetermined amount of time has elapsed, ordetermining a cumulative combination based on time and pressure, such asa time-pressure integration. The computing device 300 may monitor datafrom both the first sensor 1500 and the second sensor 3 during thistime. If the data from the second sensor 3 satisfies a threshold, forexample falls below an initiation pressure threshold value before thecounting operation completes (e.g., time elapses), the computing device300 may determine that the wearer seal check was unsatisfactory orfailed. If the data from the first sensor 1500 is above or below (orequal) to a threshold, for example a sound signal or combination ofsound signals is too high or too low before the counting operationcompletes, the computing device 300 may determine that the wearer sealcheck was unsatisfactory or failed. For example, if the wearer ismaintaining a positive or negative pressure greater than a thresholdamount relative to the ambient pressure by exhaling or inhaling whilecovering the flow paths, leakage through the respirator seal maygenerate a measurable sound or change in sound, as shown by examples inFIGS. 17-19. By using both pressure and sound measurements, thecomputing device 300 may determine that pressure can be maintainedwithout air leakage through the respirator seal. The combination ofsound signals may include signals at different frequencies. Thethresholds for either sensor may be predetermined, or may be determinedby prior data, for example data during a period before the wearer sealcheck began. In this way, the data threshold may be based at least inpart on the levels in the environment. If both the data from the firstsensor and/or the data from the second sensor satisfy the requiredthresholds and the counting operation completes, the wearer seal checkmay be determined to be satisfactory.

In some examples, a computing device may be configured to generatecomparative data based at least in part on comparing at least a portionof the first sensor data to at least a portion of the second sensordata. In some examples, a computing device may be configured to selectthe portions of first and second sensor data, wherein the first portionof the first sensor data corresponds at least in part in time to thesecond portion of second sensor data; determine the comparative databased at least in part on the first portion of first sensor data andsecond portion of second sensor data; and determine the performance ofthe respirator seal check based at least in part on the comparativedata. In some examples, the computing device may be configured todetermine that the first portion of the first sensor data satisfies afirst threshold; determine that the second portion of the second sensordata satisfies a second threshold; and determine that the first andsecond thresholds are satisfied within a substantially contemporaneoustime duration. In some examples, a substantially contemporaneous timeduration may be within 5 seconds, 10 seconds, 30 seconds, 1 minute, 5minutes, 10 minutes, 30 minutes or 60 minutes. In some examples,comparative data comprises at least one of a likelihood that therespirator seal check has passed or failed or an indication that therespirator seal check has passed or failed. In some examples, a negativepressure reusable respirator comprises at least one valve, wherein thecomputing device is configured to: determine the performance of therespirator seal check by the wearer based at least in part on data thatindicates a state of the at least one valve. In some examples, the stateof the at least one valve comprises at least one of a position of thevalve, an identifier of the valve, or data that indicates whether or adegree to which the valve is obstructed.

The computing device 300 may be configured to generate alerts at variouspoints before, during and/or after the wearer seal check process. Forexample, the computing device 300 may trigger vibrations and amberlights when a respirator is being worn and a satisfactory wearer sealcheck has not been performed, the lights and vibrations may stop, orchange color, when a wearer seal check is in process. If a wearer sealcheck is determined by computing device 200 to be unsatisfactory, thecomputing device 300 may trigger a series of red lights and vibrations,and then restart the previous amber light and vibration sequence. If awearer seal check is determined by computing device 300 to besatisfactory, a green light and single vibration may be trigger, andthen the alerts may end. Alternatively, an additional or new signalgenerated by computing device 300, such as a green light, or periodicgreen light, may occur to indicate that the satisfactory wearer sealcheck was previously completed.

In some examples of FIG. 15, a respirator seal assessment apparatus mayinclude a negative pressure reusable respirator 13, a first sensor 1500configured to generate first data indicative of sound, a second sensor 3configured to generate second data indicative of a gas characteristic ina sealed space formed by a face of a wearer. Computing device 300 may beoperatively connected to the first sensor and to the second sensor,wherein the computing device 300 may be adapted in use to determine thestart of a respirator seal assessment based at least in part on thefirst data satisfying a threshold value; begin a counting operation;monitor data from the first sensor and second data from the secondsensor, and; if the first data from the first sensor satisfies (in someexamples, falls below) a threshold value before the completion of thecounting operation OR if second data from the second sensor satisfies(in some examples, is above) a threshold value, determine that therespirator seal is unsatisfactory or has failed, or; if the first datafrom the first sensor remains above a threshold value AND if the seconddata from the second sensor is below a threshold value AND the countingoperation completes, determine that the respirator seal is satisfactoryor has passed.

In some examples of FIG. 15, sensor data (which may or may not includeacoustic sensor 1500 or data from acoustic sensor 500) may be associatedwith an assessment of respirator fit, such as a respirator fit test. Arespirator fit test may include a determination by computing device 300of the fit or seal of a respirator to a wearer's face during a firsttime period. In some embodiments, respirators, sensors and computingdevices as described herein may be used during a respirator fit test tocollect sensor data during a first time period. Sensor data, asexamples, may include data indicative of a gas characteristic in asealed space formed by a face of a wearer and a negative pressurereusable respirator, data indicative of air pressure, data indicative ofrespiratory parameters, data indicative of sound, data indicative of thepresence of particulates or gases, data indicative of valve position,data indicative of conditions present in a particular environment (e g.,sensors for measuring temperature, humidity, particulate content, noiselevels, air quality, or any variety of other characteristics ofenvironments in which respirator may be used), data indicative of motionof a wearer, data indicative of position and/or orientation of arespirator, a variety of other sensors, or combinations thereof. In someembodiments, sensor data from a first time period is associated with theresults of a respirator fit test from a first time period. For example,a set of sensor data from a first time period may be associated with a“pass” fit test result from a first time period, or a “fail” fit testresult from a first time period, or a numeric fit test result from afirst time period. In some examples, computing device 300 may storedata, such as labels or other discrete values that represent “pass” and“fail”. In some examples, confidence values that indicate the likelihoodof “pass” or “fail” may be associated with the respective labels orother discrete values. In some examples, a fit test result andassociated sensor data from a first time period includes fit testresults and associated sensor data from a set of time periods.

In some examples, an analytics engine may process sensor data from afirst time period and respirator fit test result data from a first timeperiod, along with sensor data during a second time period, in thedetermination of state and/or usage information associated with arespirator during a second time period. For instance, an analyticsengine, such as analytics service 68F of FIG. 7 (which may also beimplemented at computing device 300 of FIG. 8 or a combination ofcomputing devices in FIGS. 5, 7, 8) may apply, based at least in part onrespirator fit test result data from a first time period, the particularsensor data from a first time period to a respirator state and/or usageinformation model. The respirator state and/or usage information modelmay then be used as part of a determination of respirator state and/orusage information during a second time period. For example, sensor datafrom a first time period and respirator fit test result data from afirst time period may be used may be used, along with sensor data duringa second time period, to determine respirator state and/or usageinformation during a second time period. For example, the respiratorstate and/or usage information model may be used to determine the fitand/or seal of a respirator during respirator use in a workplace.

In some examples, while the negative pressure reusable respirator is incurrent use by the wearer, a computing device may receive the sensordata usable to determine the performance of the respirator seal check.The computing device may determine, based at least in part on the sensordata usable to determine the performance of the respirator seal checkgenerated during a fit-test that occurred prior to the current use ofthe negative pressure reusable respirator by the wearer, a performanceof a respirator seal check by the wearer. The computing device mayperform at least one operation based at least in part on the performanceof the respirator seal check.

In some examples, the respirator state and/or usage information modelmay be implemented using one or more learning, statistical, or othersuitable techniques. Example learning techniques that may be employed togenerate and/or configure models can include various learning styles,such as supervised learning, unsupervised learning, and semi-supervisedlearning. Example types of algorithms include Bayesian algorithms,Clustering algorithms, decision-tree algorithms, regularizationalgorithms, regression algorithms, instance-based algorithms, artificialneural network algorithms, deep learning algorithms, dimensionalityreduction algorithms and the like. Various examples of specificalgorithms include Bayesian Linear Regression, Boosted Decision TreeRegression, and Neural Network Regression, Back Propagation NeuralNetworks, the Apriori algorithm, K-Means Clustering, k-Nearest Neighbor(kNN), Learning Vector Quantization (LVQ), Self-Organizing Map (SOM),Locally Weighted Learning (LWL), Ridge Regression, Least AbsoluteShrinkage and Selection Operator (LASSO), Elastic Net, and Least-AngleRegression (LARS), Principal Component Analysis (PCA) and PrincipalComponent Regression (PCR). In some embodiments, an analytics engineapplies sensor data and/or respirator fit test result data from aplurality of first time periods, fit tests, workers, populations ofworkers, geographic regions, or combinations thereof to a respiratorstate and/or usage information model.

In some examples of FIG. 15 (which may or may not include acousticsensor 1500 or data from acoustic sensor 500), the respirator 13 mayinclude a mechanical mechanism, or multiple mechanical mechanisms, foraltering a flow path through a respirator, such as a valve, an actuator,a closure, or the like. In some embodiments, a mechanical mechanism maybe actuated by an air pressure differential during breathing, such as avalve. A mechanical mechanism may also by actuated by non-breathingbased mechanisms, such as by an applied external force or anelectromechanical force. In some embodiments, the mechanical mechanismmay be a shut-off valve operable between a closed position and an openposition, wherein the shut-off valve includes an actuator formed of aflange and a span extending from the flange, the span exhibiting varyingthickness such that, when operated from the open position to the closedposition, the actuator provides tactile feedback in response to anapplied force placed on the actuator, such as described in PCTPublication Number WO2015/179156, entitled RESPIRATOR NEGATIVE PRESSUREFIT CHECK DEVICES AND METHODS, filed May 11, 2015, the entire contentsof which is hereby incorporated by reference herein in its entirety. Insome embodiments, the state of a mechanical mechanism or any other datarelated to the mechanical mechanism may be communicated to a computingdevice 300, for example the position of a valve or if a mechanicalmechanism has been actuated. In some embodiments, the mechanicalmechanism may include a sensing device to sense the state of themechanical mechanism, and a computing device 300 may be configured toreceive data from a sensing device. In some embodiments, the mechanicalmechanism may be configured to block the inward flow of air into therespirator and may be actuated by a respirator wearer as part of arespirator seal check. In some embodiments, the computing device 300 maybe configured to receive state information from the mechanical mechanismand receive other sensor data associated with state and/or usageinformation of the respirator. Some examples of other sensor data mayinclude data indicative of a gas characteristic in a sealed space formedby a face of a wearer and a negative pressure reusable respirator, dataindicative of sound, data indicative of a valve position, dataindicative of proximity of facial features to a respirator, dataindicative of facial features, and the like. In some embodiments, thecomputing device 300 may configured to use state information from themechanical mechanism and other sensor data associated with state and/orusage information of the respirator in order to determine informationassociated with the performance of a respirator seal check, such as thetime of the check, the quality of the check, the quality of the seal ofthe respirator to the wearer's face, and the like.

In some examples of FIG. 15 (which may or may not include acousticsensor 1500 or data from acoustic sensor 500), the respirator 13 mayinclude one or more sensors to determine whether a wearer's mouth isopen during a seal-check or fit-test. For example, to obtain a reliableand/or accurate determination of whether a seal-check or fit-test passedor failed, it may be necessary for a wearer's mouth to be open for atleast a portion of the time during which the collection of sensor dataand/or determination of pass/fail is performed by the computing device.In some examples, apparatus 11 may include one or more sensors thatgenerate data usable to determine whether a wearer's mouth is open. Insome examples, a wearer's mouth is open when an aperture size of thewearer's mouth satisfies a threshold value (e.g., is greater than orequal to the threshold value). In some examples, sensors that generatedata usable to determine whether a wearer's mouth is open may includeone or more of an infrared sensor, optical sensor, distance sensor,temperature sensor, acoustic sensor, or any other sensor that is capableof determining whether a wearer's mouth is open. In some examples,computing device 300 may determine whether the wearer's mouth is openbased on sensor data from the one or more sensors that are capable ofdetermine whether a wearer's mouth is open. Computing device 300 maydetermine whether the wearer's mouth is open during at least a portionof a duration of a seal-check or fit-test. In some examples, computingdevice 300 may determine that the wearer's mouth is not open during atleast a portion of a duration of a seal-check or fit-test. Computingdevice 300 may determine that the seal-check or fit-test has failedbased at least in part on determining that the wearer's mouth was notopen during at least a portion of a duration of a seal-check orfit-test. In some examples, computing device 300 may determine that thewearer's mouth is open during at least a portion of a duration of aseal-check or fit-test. Computing device 300 may determine that theseal-check or fit-test has passed based at least in part on determiningthat the wearer's mouth was open during at least a portion of a durationof a seal-check or fit-test.

FIG. 16 illustrates sensor data in accordance with techniques of thisdisclosure. For example, FIG. 16 illustrates raw acoustic sensor datafrom within the sealed space of a respirator during a respirator sealcheck when (a) the respirator is improperly sealed, (b) a respiratorseal check when the respirator seal is improved, and (c) normalbreathing.

FIG. 17 illustrates sensor data in accordance with techniques of thisdisclosure. For example, FIG. 17 illustrates filtered acoustic sensordata from within the sealed space of a respirator during (a) arespirator seal check when the respirator is improperly sealed, (b) arespirator seal check when the respirator seal is improved, and (c)normal breathing.

FIG. 18 illustrates sensor data in accordance with techniques of thisdisclosure. For example, FIG. 18 illustrates filtered acoustic sensordata from within the sealed space of a respirator during (a) arespirator seal check when the respirator is improperly sealed, (b) arespirator seal check when the respirator seal is improved, and (c)normal breathing.

FIG. 19 illustrates sensor data in accordance with techniques of thisdisclosure. For example, FIG. 19 illustrates combination of acousticsensor data from an acoustic sensor of a respirator filtered atdifferent frequency bands.

FIG. 20 illustrates sensor data in accordance with techniques of thisdisclosure. For example, FIG. 20 illustrates exemplary pressure dataindicative of whether a respirator is being worn and indicative of theoccurrence of a respirator seal check.

The techniques, systems, components, and apparatuses in any of thedisclosed examples of the various FIGS. may be employed in a variety ofmeans towards assessing the seal of a respirator. For example,implementations in any of the example FIGS. described for a wearer sealcheck may also be used for a user seal check, a respirator fit check, arespirator fit test, and/or other use cases for assessing the seal of arespirator.

Although the methods and systems of the present disclosure have beendescribed with reference to specific exemplary embodiments, those ofordinary skill in the art will readily appreciate that changes andmodifications may be made thereto without departing from the spirit andscope of the present disclosure.

In the present detailed description of the preferred embodiments,reference is made to the accompanying drawings, which illustratespecific embodiments in which the invention may be practiced. Theillustrated embodiments are not intended to be exhaustive of allembodiments according to the invention. It is to be understood thatother embodiments may be utilized and structural or logical changes maybe made without departing from the scope of the present invention. Thefollowing detailed description, therefore, is not to be taken in alimiting sense, and the scope of the present invention is defined by theappended claims.

The techniques of this disclosure may be implemented in a wide varietyof computer devices, such as servers, laptop computers, desktopcomputers, notebook computers, tablet computers, hand-held computers,smart phones, and the like. Any components, modules or units have beendescribed to emphasize functional aspects and do not necessarily requirerealization by different hardware units. The techniques described hereinmay also be implemented in hardware, software, firmware, or anycombination thereof. Any features described as modules, units orcomponents may be implemented together in an integrated logic device orseparately as discrete but interoperable logic devices. In some cases,various features may be implemented as an integrated circuit device,such as an integrated circuit chip or chipset. Additionally, although anumber of distinct modules have been described throughout thisdescription, many of which perform unique functions, all the functionsof all of the modules may be combined into a single module, or evensplit into further additional modules. The modules described herein areonly exemplary and have been described as such for better ease ofunderstanding.

If implemented in software, the techniques may be realized at least inpart by a computer-readable medium comprising instructions that, whenexecuted in a processor, performs one or more of the methods describedabove. The computer-readable medium may comprise a tangiblecomputer-readable storage medium and may form part of a computer programproduct, which may include packaging materials. The computer-readablestorage medium may comprise random access memory (RAM) such assynchronous dynamic random access memory (SDRAM), read-only memory(ROM), non-volatile random access memory (NVRAM), electrically erasableprogrammable read-only memory (EEPROM), FLASH memory, magnetic oroptical data storage media, and the like. The computer-readable storagemedium may also comprise a non-volatile storage device, such as ahard-disk, magnetic tape, a compact disk (CD), digital versatile disk(DVD), Blu-ray disk, holographic data storage media, or othernon-volatile storage device.

The term “processor,” as used herein may refer to any of the foregoingstructure or any other structure suitable for implementation of thetechniques described herein. In addition, in some aspects, thefunctionality described herein may be provided within dedicated softwaremodules or hardware modules configured for performing the techniques ofthis disclosure. Even if implemented in software, the techniques may usehardware such as a processor to execute the software, and a memory tostore the software. In any such cases, the computers described hereinmay define a specific machine that is capable of executing the specificfunctions described herein. Also, the techniques could be fullyimplemented in one or more circuits or logic elements, which could alsobe considered a processor.

1-71. (canceled)
 72. A system comprising: a negative pressure reusablerespirator configured to be worn by a wearer and to cover at least amouth and a nose of the wearer to form a sealed space formed by a faceof the wearer and the negative pressure reusable respirator; a firstsensor configured to generate first sensor data indicative of a gascharacteristic in a sealed space formed by a face of the wearer and thenegative pressure reusable respirator; a second sensor configured togenerate second sensor data indicative of sound; at least one computingdevice configured to: determine, based at least in part on the firstsensor data and the second sensor data, a performance of a respiratorseal check by the wearer; and perform at least one operation based atleast in part on the performance of the respirator seal check.
 73. Thesystem of claim 72, wherein the performance of the respirator seal checkindicates whether the respirator seal check has passed or failed. 74.The system of claim 72, wherein the performance of the respirator sealcheck indicates a degree of leakage of air external to the sealed spaceinto the sealed space.
 75. The system of claim 72, wherein the at leastone computing device is configured to generate comparative data based atleast in part on comparing at least a portion of the first sensor datato at least a portion of the second sensor data.
 76. The system of claim72, wherein the at least one computing device is configured to: selectthe portions of first and second sensor data, wherein the first portionof the first sensor data corresponds at least in part in time to thesecond portion of second sensor data; determine the comparative databased at least in part on the first portion of first sensor data andsecond portion of second sensor data; and determine the performance ofthe respirator seal check based at least in part on the comparativedata.
 77. The system of claim 76, wherein to determine the comparativedata based at least in part on the first portion of first sensor dataand second portion of second sensor data, the computing device isconfigured to: determine that the first portion of the first sensor datasatisfies a first threshold; determine that the second portion of thesecond sensor data satisfies a second threshold; and determine that thefirst and second thresholds are satisfied within a substantiallycontemporaneous time duration.
 78. The system of claim 76, wherein thecomparative data comprises at least one of a likelihood that therespirator seal check has passed or failed or an indication that therespirator seal check has passed or failed.
 79. The system of claim 72,wherein the negative pressure reusable respirator comprises at least onevalve, wherein the computing device is configured to: determine theperformance of the respirator seal check by the wearer based at least inpart on data that indicates a state of the at least one valve.
 80. Thesystem of claim 79, wherein the state of the at least one valvecomprises at least one of a position of the valve, an identifier of thevalve, or data that indicates whether or a degree to which the valve isobstructed.
 81. The system of claim 80, wherein to perform the at leastone operation based at least in part on the performance of therespirator seal check, the at least one computing device is configuredto generate an output comprising at least one of a message for at leastone other computing device or a visual, audible, or haptic output at anoutput interface.
 83. A computing device comprising: at least oneprocessor; and a memory comprising instructions that, when executed bythe at least one processor, cause the at least one processor to:receive, from a first sensor, first sensor data indicative of a gascharacteristic in a sealed space formed by a face of the wearer and anegative pressure reusable respirator, wherein the negative pressurereusable respirator is configured to be worn by the wearer and to coverat least the mouth and the nose of the wearer to form a sealed spaceformed by the face of the wearer and the negative pressure reusablerespirator; receive, from a second sensor, second sensor data indicativeof sound; determine, based at least in part on the first sensor data andthe second sensor data, a performance of a respirator seal check by thewearer; and perform at least one operation based at least in part on theperformance of the respirator seal check.
 84. The computing device ofclaim 83, wherein the performance of the respirator seal check indicateswhether the respirator seal check has passed or failed.
 85. Thecomputing of claim 83, wherein the performance of the respirator sealcheck indicates a degree of leakage of air external to the sealed spaceinto the sealed space.
 86. The computing device of claim 83, wherein thememory comprises instructions that, when executed by the at least oneprocessor, cause the at least one processor to generate comparative databased at least in part on comparing at least a portion of the firstsensor data to at least a portion of the second sensor data.
 87. Thesystem of claim 86, wherein the memory comprises instructions that, whenexecuted by the at least one processor, cause the at least one processorto: select the portions of first and second sensor data, wherein thefirst portion of the first sensor data corresponds at least in part intime to the second portion of second sensor data; determine thecomparative data based at least in part on the first portion of firstsensor data and second portion of second sensor data; and determine theperformance of the respirator seal check based at least in part on thecomparative data.
 88. The system of claim 87, wherein to determine thecomparative data based at least in part on the first portion of firstsensor data and second portion of second sensor data, the memorycomprises instructions that, when executed by the at least oneprocessor, cause the at least one processor to: determine that the firstportion of the first sensor data satisfies a first threshold; determinethat the second portion of the second sensor data satisfies a secondthreshold; and determine that the first and second thresholds aresatisfied within a substantially contemporaneous time duration.
 89. Thesystem of claim 88, wherein the comparative data comprises at least oneof a likelihood that the respirator seal check has passed or failed oran indication that the respirator seal check has passed or failed. 90.The system of claim 83, wherein the negative pressure reusablerespirator comprises at least one valve, wherein the computing device isconfigured to: determine the performance of the respirator seal check bythe wearer based at least in part on data that indicates a state of theat least one valve.
 91. The system of claim 83, wherein the state of theat least one valve comprises at least one of a position of the valve, anidentifier of the valve, or data that indicates whether or a degree towhich the valve is obstructed.
 92. The system of claim 91, wherein toperform the at least one operation based at least in part on theperformance of the respirator seal check, the memory comprisesinstructions that, when executed by the at least one processor, causethe at least one processor to generate an output comprising at least oneof a message for at least one other computing device or a visual,audible, or haptic output at an output interface.